text:
\section{Conclusion} \label{s:conclusion}

Using words alone, it is possible to identify the time period that a document is
about (via the Wikipedia datasets) or the time period in which it was written
(via the Gutenberg dataset). In the former case, the presence of named entities
dominates the texts, and their names provide strong evidence for particular
historical periods. For the latter, the texts are fictional (including science
fiction), and they rarely mention historical entities. For these, general terms
that are indicative of a given time period dominate the prediction.
Interestingly, the models that are used (successfully) for this later task are
trained on Wikipedia biographies about historical individuals, but which were
written in the last decade.

The predictions made by our models provide a natural counterpart to other
temporally sensitive models of word choice, such as Dynamic Topic Models (DTMs)
~\cite{Blei:Lafferty:2006}. DTMs assume that documents are labeled with dates;
our model could thus be used to create labels for an otherwise un-dated set of
documents which can then be analyzed with DTMs. An important aspect of our work is that it opens
opportunities for analyzing sub-parts of documents, such as chapters, sections
and paragraphs of books. Consider, for example, Samuel Goodrich's ``The Second Book of History''
from 1840, which covers thousands of years of history for many parts of the
world.

Of course, many texts include explicit dates, and exploiting their presence via
approaches such as~\shortcite{chambers:doctimestamps} would only strengthen our predictions. Also,
they create opportunities for using weaker, but more pin-pointed, supervision:  strings identified as dates with
high-confidence can be pivots for learning word distributions. This would
obviate the need for labeled training material such as Wikipedia biographies,
and thereby enable our methods to be used and adapted for a wide variety of
genres. Given decent temporal expression identifiers for other languages, this
could be used to bootstrap models for more languages as well.

\section{Document Collections} \label{s:data}

Our models are trained and evaluated on three datasets \footnote{All three
will be released upon publication, including processing and extraction needed
for replication of experiments.}

\textbf{Wikipedia biographies (wiki-bio)}. The Wikipedia dump of English on
September 4, 2010 are used \footnote{\small
\url{http://download.wikimedia.org/enwiki/20100904/enwiki-20100904-pages-articles.xml.bz2}}
to obtain biographies of individuals who lived between the years 3800 B.C.\ to
2010 A.D.

We extract the lifetime of each individual via each article's \emph{Infobox}
\texttt{birth\_date} and \texttt{death\_date} fields. We exclude biographies
which do not specify one of the fields or which fall outside the year range
considered.  If the birth date is missing, we approximate it as 100 years before
the death date (similarly and conversely when the death date is missing).
We perform this only to estimate the word distributions in the training set.
All such documents are discarded for validation and test.
We treat the life span of each individual as the article's labeled time span. Note
that the distribution of biographies is quite skewed toward recent times, as
shown in  \fref{birth histogram}.

\begin{figure}
\begin{center}
  \includegraphics[width=0.5\textwidth]{WikiBirthCounts.png}
\caption{Graph of number of births per year in the Wikipedia biography training
set.}
\label{fig:birth histogram}
\end{center}
\end{figure}
\begin{table}
\begin{center}
{\small
\begin{tabular}{c|p{5.8cm}}
Year & \multicolumn{1}{c}{Sample Text} \\ \hline
  \multirow{5}{*}{400 B.C.}
 & The Carthaginians occupy Malta.\\
 & War breaks out between Sparta and Elis.\\
 & San Lorenzo Tenochtitlán is abandoned.\\
 & Thucydides, Greek historian dies.\\
 & The catapult is invented by Greek engineers.\\\hline
\multirow{5}{*}{50 A.D.}
 & Claudius adopts Nero.\\
 & Phaedrus, Roman fabulist dies.\\
 & The Epistle to the Romans is written.\\
 & Abgarus of Edessa, king of Osroene dies.\\
 & Hero of Alexandria invents steam turbine.\\
 \hline
 \multirow{5}{*}{1000 A.D.}
 & Dhaka, Bangladesh, is founded.\\
 & The Diocese of Kołobrzeg is founded.\\
 & Garcia IV of Pamplona dies\\
 & Gunpowder is invented in China.\\
 & Middle Horizon period ends in the Andes.\\\hline
\multirow{5}{*}{2000 A.D.}
 & Tate Modern Gallery opens in London.\\
 & Tuvalu joins the United Nations.\\
 & The last Mini is produced in Longbridge.\\
 & The Constitution of Finland rewritten.\\
 & Patrick O'Brian, English writer dies.\\
 \hline
\end{tabular}
}
\end{center}
\caption{Sample text from 5 different years in wiki-year dataset.}
\label{tab:sample-wiki-years}
\end{table}

The resulting dataset contains a total of 280,867 Wikipedia biographies of individuals
whose lifetimes begin and end within the year range considered (3800
B.C. to 2010 A.D.). These biographies are randomly split into subsets
for training, development, and testing.  We remove documents from development and test
sets if either their \texttt{birth\_date} or \texttt{death\_date} missing. This
leaves us with 224,476 training articles, 8,358 development articles and 8,440
test articles.

\textbf{Wiki-year pages (wiki-year)}. Wikipedia has a collection of pages
corresponding to various years that describe the events that occurred for a given year.
\footnote{\url{http://en.wikipedia.org/wiki/List_of_years}}.
Each page has the corresponding year as its label and the text
contains all the events that occurred in that year -- some examples are shown in
\tref{sample-wiki-years}. Pages for years before 500 B.C. at times contain
events that span several years, so we restrict the documents to be those from
500 B.C. to 2010 A.D.\footnote{For example the events ``Proto-Greek invasions of
Greece.'', ``Minoan Old Palace (Protopalatial) period starts in Crete.'' etc.
are present in the text for 1878 as well as 1880 B.C. These occurred around 1880
B.C. but their exact occurrence date is unknown.} The 2,511 documents for this
span are divided into even years for development (1256 documents) and odd years
for testing (1255 documents).

Table~\ref{tab:sample-wiki-years} shows random sample lines from four wiki-year
pages. The lines are terse and the text as a whole contain very little temporal
expressions.

\textbf{Gutenberg short stories (gutss)}. We collected 678
English short stories published between 1798 to 2008, obtained from the Gutenberg Project.
Whereas with Wikipedia biographies we use labeled time spans corresponding to
lifetimes, Gutenberg stories are labeled by publication year. The average,
minimum and maximum word count of these stories are (roughly) 14,000, 11,000 and
100,000 respectively. Stories are randomly split into a development and test set
of 333 and 345 documents, respectively.

\textbf{Notation}. We refer to
biographies, stories and Wiki-Year pages alike as {\em documents}, and each
dataset as defining a document {\em collection} $c$ consisting of $N$ documents:
$c=d_{1:N}$.

\section{Experimental Setup} \label{s:evalsetup}
\label{sec:metrics}

\paragraph{Data.} To test the ability of word-based models to predict timestamps
for documents, all temporal expressions identified in each document using the
Heidel-Time temporal tagger~\cite{HeidelTime} are removed. All numeric tokens
and standard stopwords are also removed. The remaining tokens produce a
vocabulary of 374,973 words for the entire Wikipedia biography corpus.
Heidel-Time also provides the first two dates present in the text, which we use
as a strong baseline for the biography task.

\paragraph{Tuning and smoothing} For each model+task, we tune the parameters
$\delta$, $\mu$, $\xi$, and $\lambda$ over the development sets of the
corresponding dataset. As in prior work~\cite{deJong05,Kanhabua08ecdl,Kumar11-cikm}, we smooth chronon
pseudo-document language models (for all models as well as smoothing techniques)
but not document models. While smoothing both may potentially help, smoothing
the former is strictly necessary for KL-divergence to prevent division by zero.

\paragraph{Target predictions} For Wikipedia biographies, the predicted $\hat{y}$
represents the mid-point of the individual's life span; for wiki-years,
it is the year of the events on the page, and for Gutenberg short stories it
is the publication date of the story. In later sections we will present the baseline
predictions for $\hat{y}$ for each dataset.

\paragraph{Error Measurement} When predicting a single year for a document, a natural
error measure between the predicted year $\hat{y}$ (mid-point) and the actual
year $y^*$ is the difference $|\hat{y}-y^*|$. We compute this difference for
each document, then compute and report the mean $\bar{y}$ and median {\bf
$\tilde{y}$} of differences across documents. Similar distance error measures
have also been used with document geolocation
\cite{eisenstein10,wing-baldridge:2011:ACL}.

\paragraph{Baselines} For Wikipedia biographies the first baseline
(\textbf{baseline-ht}) is the mid-point of the first two temporal-dates extracted
by Heidel-Time~\cite{HeidelTime}. This is a highly effective baseline since
it is often the case in Wikipedia biographies that the first
two dates are the birth and death dates. The second
baseline  for biographies is to always predict the year that has
greatest number of biographies spanning it, which is 1915 (\textbf{baseline-1915}).
For Gutenberg stories, we take 1903, the
midpoint of the range of publication dates (1798-2008) as the baseline
(\textbf{baseline-1903}). For wiki-years, the baseline is the midpoint of the
prediction range i.e. $\frac{-500+2010}{2} = 755$ (\textbf{baseline-755}).
This assumes that one knows a rough range of possible publication dates, which
is reasonable for many applications and thus provides a good reference for comparison.

We also report \textbf{oracle error} which is the
mean and median error which would occur if a model always picked the correct
chronon. This error arises because chronons span multiple years; large chronons
in particular will have higher oracle error (but may perform better for actual
prediction due to better model estimation).

\section{Results}
\label{sec:exps}

\subsection{Parameter tuning}

We begin with year prediction experiments on the development sets to
tune the parameters $\delta$, $\xi$ or $\mu$. We parametrize $\mu$ as a
function of the average chronon size in the training set:

\begin{equation}
\mu = \lceil\rho\bar{c}\rceil
\end{equation}

\noindent
$\bar{c}$ is a constant whose value is dependent upon the model and the task.
The value of $\rho$ is tuned over the validation set.

\paragraph{Choice of chronon size and smoothing parameters.}  We tune the chronon
size ($\delta$) over the validation set and tune the smoothing parameters
$\lambda$, $\rho$, and $\xi$ (depending on the type of smoothing) for the
best $\delta$ obtained. For $\delta$ tuning we assign an arbitrary value to the
smoothing parameter $\lambda$. The $\delta$ is tuned for each dataset and KL
model with CS and JM smoothings. DL model with Dirichlet/JM smoothing and
KL model with Dirichlet smoothing use the same best $\delta$ obtained for KL model
with JM smoothing on the respective datasets. For each dataset, model and smoothing
triad, the smoothing parameter $\lambda$, $\xi$, or $\rho$ is tuned. Tuning is
performed to minimize the mean error on the development sets. The search space
for smoothing parameters $\xi$, $\lambda$
and $\rho$ includes \{ $1e-12$, $1e-11$, \ldots, 0.1, 0.25, 0.75, 0.9, 0.99, \ldots, 0.999999999 \}

Figures~\ref{fig:tuning-wiki-bio-years-delta} and~\ref{fig:tuning-wiki-bio-years-para} shows the tuning of
$\delta$ and smoothing parameters ($\lambda$ for JM and $\xi$ for CS) for the wiki-bio and
wiki-years dataset. All triplets formed by KL/DL model $\times$ JM/Dirichlet
smoothing $\times$ wiki-years/wiki-bio/gutss dataset use the optimum
chronon-size obtained for the respective datasets from the KL model with JM smoothing.

From Figure~\ref{fig:tuning-wiki-bio-years-para} the mean error curve is generally
smooth for $\lambda$ and $\xi$ unlike the $\delta$, chronon-size parameter
(figure~\ref{fig:tuning-wiki-bio-years-delta}). This makes smoothing the LMs robust to a range of values.
The $\delta$ has more fluctuation even in the optimal neighborhood, which makes tuning chronon-size
more critical. A straightforward strategy to reduce this sensitivity is to
smooth chronon models based on the word distributions of neighboring chronons
as well as interpolating with the collection model, which we intend to explore
in future. The optimal chronon sizes for the three datasets are 10 years for
wiki-bio and gutss and 50 years for wiki-year.

\subsection{Test results.}

Table~\ref{tab:test-results} shows the results for the various models on the
test sets for all three datasets, using the parameters tuned on the
corresponding development sets.

\paragraph{Wiki-bio}
The models beat both baselines easily. Note that baseline-ht is quite
strong for a large number of documents: it gives a median error of zero since
over half of the documents have birth and death dates as their first dates.
Nonetheless, it fails entirely for many documents, and obviously has limited
applicability. The models all reduce error by one half in comparison to
baseline-1915. The best model (DL + JM smoothing) achieves a mean error of 37.4
years, which is quite strong given that the prediction range is 5810 years.  The
mean oracle error for the best model is 2.5 years. The mean and median error was
36.6 and 22.0 years for the best performing model (DL + JM smoothing) on the
development set.

\paragraph{Wiki-years}
The models beat baseline-755 comfortably. Despite the fact that the documents
are relatively short and that any given document contains a number of often
unrelated events (and thus low counts per word type), the results are in line
with those for wiki-bio, with mean error of 37.9 and median error of 20 years
for the best models. The mean oracle error, 12.4 years, for this dataset is
higher due to the larger chronon size. The KL model with JM smoothing provided
the best mean and median error of 36.7 and 21.0 years respectively over
development set.

\paragraph{Gutss} All models except the one that uses chronon-specific smoothing
with KL-divergence outperform baseline-1905 on mean error, and even that one is
better on median. Since these are works of fiction with few historical entities
mentioned, the mean error of 22.9 and median error of 19.0 of the best models
indicate that the approach is quite capable of exploiting implicit temporal cues
of basic vocabulary choices. Also, recall that the model is trained on Wikipedia;
this demonstrates that this choice of training set works well as the basis for
predictions on other domains. The mean oracle error (for chronons of 10 years)
is 2.5 years. For the development set, the mean and median error was 20.4 and
17.0 years for the best performing model (DL + JM smoothing).

\begin{table}[h]
\begin{center}
\scalebox{1.0}{
\begin{tabular}{l|l||c|c}
Data & Model(Smooth.) & $\bar{y}$ & $\tilde{y}$
\\
\hline
\multirow{7}{1mm}{\begin{sideways}\parbox{15mm}{wiki-bio}\end{sideways}}
& baseline-ht 	&  306.6  &  0.0 \\
& baseline-1915   &  81.1  &  38.5 \\
& KL($\xi$=$10^{-4}$) &  42.8  &  22.5 \\
& KL($\lambda$=0.999) &\bf  37.4  &  22.5  \\
& KL($\rho$=$10^{-6}$) &  38.1  & \bf 22.0  \\
& DL($\lambda$=0.999) & \textbf{\textit{37.4}}  &  \textit{22.5} \\
& DL($\rho$=$10^{-6}$) &  38.0  &  \bf 22.0 \\
\hline
\multirow{6}{1mm}{\begin{sideways}\parbox{15mm}{wiki-year}\end{sideways}}
& baseline-755 	    & 627 & 627 \\%& 978 & 489 \\
& KL($\xi$=0.99) & 143.6  & 30.0  \\
& KL($\lambda$=0.25) &  \textbf{\textit{37.9}}  & \textbf{\textit{20.0}}  \\
& KL($\rho$=0.01) & 60.6   & 22.0 \\
& DL($\lambda$=0.50) & \bf 37.9  & \bf 20.0 \\
& DL($\rho$=0.01) &  52.1 &  \bf 20.0 \\
\hline
\multirow{6}{1mm}{\begin{sideways}\parbox{15mm}{gutss}\end{sideways}}
& baseline-1905 	 		 & 37 & 50 \\
& KL($\xi$=$10^{-3}$) & 39.6  & \bf 19.0  \\
& KL($\lambda$=0.999) & \bf 22.9  & \bf 19.0  \\
& KL($\rho$=$10^{-6}$) & 37.3   & 22.0  \\
& DL($\lambda$=0.999) & \textbf{\textit{22.9}}   & \textbf{\textit{19.0}} \\
& DL($\rho$=$10^{-6}$) &  37.4  &  23.0
\end{tabular}
}
\end{center}
\caption{Test set results. $\lambda$=JM, $\xi$=CS, and
$\rho$=Dirichlet smoothing. DL uses the non-uniform chronon prior. The best
results are bolded, and the results of the best model on the corresponding
development set are italicized.}
\label{tab:test-results}
\end{table}

\subsection{Output analysis}

Using the output on the development set, we find interesting patterns in the
predictions made by the models and the way they use the words as evidence.

\paragraph{Time warps}

\shortcite{flickRwormholes:2010} used geotags on Flickr
images to identify wormholes---locations that are not physically near but
which are nonetheless similar to one another. We observe some similar
patterns, in our case {\it time warps}, in our dataset.
These are particularly prominent in wiki-year documents due to their
terseness as these are list of events that happened in a given year.
Besides the models trained on wiki-bio
set add to this phenomenon as the context for the two datasets are
slightly different. A cluster of dev event years from between 250 to
150 A.D. (e.g. wiki-years 234, 214, 152, 156 etc.) are predicted to be
in 2nd century B.C. (200 B.C. to 150 B.C.) by our model.  These event
years are very short with an average length of 40-50 words per
document. The discriminatory tokens present in these texts include: {\it
  Roman, Empire, Kingdom, Han, Dynasty, China, Selucid, Greek,
  etc.}. In the 200-150 B.C. period, all the documents in
training set are about Greek/Selucid, Roman and Chinese (mostly from
Han dynasty) emperors/personalities (e.g. Attalus I, Eratosthenes,
Plautus, Emperor Gaozu of Han, Emperor Hui of Han, Zhang Qian, Emperor
Wen of Han etc.) and contain similar prominent terms as the wiki-year
event texts. This common collection of terms pushes the model to resolve
wiki-year texts to 2nd century B.C. This happens because of the relative
frequency of such terms in B.C. and A.D.: although these terms are
present in the A.D. chronons, their
proportion with respect to other terms is much smaller. Test documents
that contain these terms are thus attracted to the B.C. chronons since
they have these terms in generally higher proportion.

\begin{table*}
\begin{center}
\begin{tabular}{c|c|c|c|c}
\hline
meriwether & komatsu & capote & cranmer & payload \\ \hline
morelos & kido & stopes & sap & laila \\ \hline
hem & shakuntala & anthrax & scooby & crayon \\ \hline
plutarch & sampaguita & woodbury & untimely & teleplay \\ \hline
tele & electorates & derivatives & polygram & wavelength \\ \hline
\end{tabular}
\end{center}
\caption{ Top 25 most predicitve words in descending
order (left to right and top to bottom) from wiki-bio dev set. }
\label{tab:top20-words}
\end{table*}

\begin{table*}
\begin{center}
\begin{tabular}{c|c|c|c|c}
\hline
oneself & primari & ssu & thebes & porphyry \\ \hline
lysias & confucius & morality & romana & matteo \\ \hline
unbroken & goodness & timpul & tarii & grout \\ \hline
sinop & cynical & tub & crates & lantern \\ \hline
bite & phila & transaction & corporeal& conciliation \\ \hline

\end{tabular}
\end{center}
\caption{ Bottom 25 least predicitve words in descending
order (left to right and top to bottom) from wiki-bio dev set. }
\label{tab:bottom20-words}
\end{table*}

Another interesting cluster is short documents containing
similar terms from 200-800 A.D. that are resolved to the mid-6th century A.D. The short
wiki-year texts (e.g. years 246, 486, 750, 822, etc.) contain co-occurring
set of terms like {\it Byzantine, Empire, Roman, Arab, Conquest, Islam}, and {\it Caliphate}. These
short year events text contain events
related to mostly Byzantine wars, emperors, Islamic/Arab conquest, Caliphates
etc. These are resolved to the mid-6th century A.D. period that predominantly contains
biographies of Islamic Caliphates (e.g. Abd al-Malik, Abu Bakr, Ali, Umar etc.)
and Byzantine emperors and prominent personalities (e.g. Maurice, Fausta,
Constans II etc.) which has predominant terms such as: {\it Byzantine, Empire,
Caliph, Islam}, and {\it conquest}.

\paragraph{Discriminative Words }
Table~\ref{tab:top20-words} and~\ref{tab:bottom20-words} shows the top and
bottom 25 words in the descending order of their strengths, where the predictive strength score
of a word $w$ is calculated as average prediction error of all the documents that contain the
word $w$. The majority of the words that are most predictive are uncommon nouns, especially
uncommon last names or famous titles e.g. {\it capote}, {\it komatsu}, and {\it cranmer}.
Words such as {\it tele}, {\it wavelength}, {\it electorates},
{\it teleplay}, {\it sap} (the company) also have strong temporal connection as
these have never been used before 19th century. The
least predictive ones are mostly common words such as {\it
goodness}, {\it oneself}, {\it morality}, {\it tub}, {\it crates}, and {\it lantern}. The
uncommon words among the least predictive are generally present in just one
or two documents for which our model performs very poorly. It is highly likely that these words
might be inducing those warps due to their predominance and uniqueness.

\section{Introduction} \label{s:intro}

Temporal analysis of text has been an active area of research since the early
days of text mining with different focus in different disciplines.
In early computational linguistics research it was primarily concerned
with the fine-grained ordering of temporal events
\cite{Allen:1983,Vilain:Beranek:1982}. Information retrieval research has
focused largely on time-sensitive document ranking~\cite{Dakka10,Li03cikm},
temporal organization of search results~\cite{AlonsoCIKM09},
and how queries and documents change over time~\cite{Kulkarni11wsdm}.

This paper explores temporal analysis models that use ideas present in
both computational linguistics and information retrieval. While some
prior research has focused on extracting explicit mentions of temporal
expressions~\cite{AlonsoCIKM09}, we investigate the feasibility of
using text alone to assign timestamps to documents. Following previous
document dating work~\cite{deJong05,Kanhabua08ecdl,Kumar11-cikm}, we
construct supervised language models that capture the temporal
distribution of words over {\it chronons}, which are contiguous atomic
time spans used to discretized the timeline.  Each chronon model is
smoothed by interpolation with the entire training set collection. For
each test document, a unigram language model is computed and used to
find the document's similarity with each chronon's language
model. This provides a ranking over chronons for the document,
representing the document's likelihood of being similar to the time
periods covered by each chronon~\cite{deJong05,Kanhabua08ecdl}.

Our chronon models are learned from Wikipedia biographies spanning 3800 B.C. to 2010 A.D.
Wikipedia-based training is
advantageous since its recency enables us to control against stylistic vs.
content factors influencing vocabulary use (e.g. consider the difference between
William Mavor's 1796 discussion\footnote{\url{http://bit.ly/lKR8Aa}} of Sir
Walter Raleigh vs. a modern retrospective
biography\footnote{\url{http://en.wikipedia.org/wiki/Walter_Raleigh}}). This
contrasts with resources such as the Google n-grams corpus
\cite{GoogleN-Grams:2011}, which is based on publication dates, and thus
reflects information about when a document was written rather than what it is
about.

Our methods, all of which use the Wikipedia biographies for training models, are
evaluated on three tasks. The first is matched to the training data: predict the
mid-point of an individual's life based on the text in his or her Wikipedia
biography. Our best model achieves a median error of 22 years and a mean error
of 36 years. The second task is to predict the year for a set of events between
500 B.C. and 2010 A.D., using Wikipedia's pages for events in each
year.\footnote{\url{http://en.wikipedia.org/wiki/List_of_years}} The best model
gives a mean error of 36 years and median error of 21 years. The final task is
predicting the publication dates of short stories from the Gutenberg project
from the period 1798 to 2008.\footnote{\url{http://www.gutenberg.org}} In
comparison to biographies, these stories have far fewer mentions of historical
named entities that with peaked time signatures useful for prediction. This,
plus the difference in genre between Wikipedia biographies (training) and works
of fiction, stand to make this task more challenging. However, the distributions
learned from the biographies prove to be quite robust here: our best model
achieves a mean error of 20 years and a median error of 17 years from the true
publication date.

Our primary contribution is demonstrating the robustness and informativity of
the implicit temporal cues available in text alone, across a diverse set of
three prediction tasks.  We do so for document collections spanning hundreds and
thousands of years, whereas previous work has generally focused on relatively
short periods (decades) for recent time spans. Note that we use a robust
temporal expression identifier for English, Heidel-Time \cite{HeidelTime}, to
identify and remove dates from all texts for both training and testing. While
one could exploit a resource such as Heidel-Time to perform rule-based document
dating (possibly in combination with our methods and others such as \cite{chambers:doctimestamps}),
this work demonstrates that text-based techniques can be used effectively for languages for which
such temporal extraction resources are not available (Heidel-Time has resources only for
English, German and Dutch).

A second contribution is a thorough exploration of the information retrieval
approach for this task, including consideration of three different techniques
for smoothing chronon language models and a comparison of generative
(document-likelihood) and KL-divergence models for identifying the best chronon
for a test document. We find that straightforward Jelenik-Mercer smoothing
(basic linear interpolation) works the best, and that both document likelihood
and KL-divergence based approaches perform similarly.

A specific task of interest in digital humanities is to identify and visualize
text sequences relating to the same time period across a collection of books. Our approach can
be used to timestamp subsequences of documents, which could be book-length
narratives or fictions, without explicit dates.

\section*{Acknowledgments}
This work was partially supported by a grant from the Morris
Memorial Trust Fund of the New York Community Trust and a Temple Fellowship.

\bibliographystyle{acl}

\section{Model} \label{s:models}

Similar to previous work, we represent continuous time via
discrete units. Our formalization most closely follows that of Alonso et
 al.~\shortcite{AlonsoCIKM09}. The smallest temporal granularity we consider in
 this work is a single year.

\subsection{Estimation} \label{s:represent}

Let a {\em span} of multiple, contiguous years be some interval $\tau
= [y_s,y_e]$, where $y_s$ and $y_e$ refer to start and end years,
respectively. As noted in \S\ref{s:data}, we also know the year range covered by
each document collection and restrict our overall timeline correspondingly to
the span $\tau_o = [y_0,y_Y)$, covering a total of $y_Y-y_0=\Delta$ years.

A {\em chronon} is an atomic interval $x$ upon which a discrete timeline
is constructed \cite{AlonsoCIKM09}. In this paper, a chronon consists
of $\mathbf{\delta}$ years, where $\delta$ is a tunable parameter.
Given $\delta$, the timeline $T_\delta$ is decomposed into a sequence
of $n$ contiguous, non-overlapping chronons $\mathbf{x} = x_{1:n}$,
where $n=\frac{\Delta}{\delta}$.

A ``pseudo-document'' $d^x$ is created for each
chronon $x$ as the concatenation of all training documents whose labeled
span overlaps $x$. For example, for a chronon size $\delta$=25 years, the
biography of Abraham Lincoln (1809-1865) is included in pseudo-documents for each of the
chronons representing 1800-1825, 1826-1850, and 1851-1875.

\label{s:smoothing}

A chronon model  $\Theta^x$ is estimated from the pseudo-document $d^x$ and
smoothed via interpolation with the collection. Chronon models are smoothed in
three ways: a) Jelinek-Mercer smoothing (JM) \cite{Zhai04}, b) Dirichlet
smoothing ~\cite{Zhai04}, and c) chronon-specific smoothing (CS)
\cite{Kumar11-cikm}. For all three, for each word $w$, $\hat{\Theta^d_w}$ can be
computed as a mixture of document $d$ and document collection $c$
maximum-likelihood (ML) estimates:
\begin{equation}
\hat{\Theta^d_w} = \lambda \frac{f^d_w}{|d|} + (1-\lambda) \frac{f^c_w}{|c|}~,
\end{equation}
where $f^d_w$ and $f^c_w$ denote the frequency of word $w$ in the document or
collection respectively, $|d|$ and $|c|$ are the document and collection
lengths, and the parameter $\lambda$ specifies the smoothing strength.  In
case of Jelenik-Mercer smoothing, the value of $\lambda$ is chosen directly via
tuning over values from zero to one.

With Dirichlet smoothing, $\lambda$ is chosen as:
\begin{equation}
\lambda=\frac{|d|}{|d| + \mu}
\end{equation}
$\mu$ is a hyper-parameter tuned on the development set.

Chronon-specific smoothing, in turn, is a special case of Dirichlet smoothing where:
\begin{equation}
\mu=\frac{\xi}{|V_{d^x}\cup V_{d_i}|}
\end{equation}
where $|V_{d^x}\cup V_{d}|$ denotes the
document-chronon specific vocabulary for some collection document $d_i$ and
pseudo-document $d^x$ and $\xi$ is a prior for hyper-parameter $\mu$ that is tuned on the development set.

\subsection{Estimation}

We calculate the affinity between each chronon $x$ and a document $d$ by
estimating the discrete distribution $P(x|d)$. In the next section, we use
$P(x|d)$ to infer affinity between $d$ and different chronons. The mid-point of
(see section~\ref{s:represent}) the most likely chronon is then returned as the
predicted year by the model. We define two primary models for estimating
$P(x|d)$. The first approach estimates the likelihood of $d$ for each chronon;
via Bayes rule, this is combined with a chronon prior to calculate the
likelihood of each chronon for $d$. The second approach ranks chronons based on
the divergence between latent unigram distributions $P(w|d)$ and
$P(w|x)$~\cite{lafferty2001document}.

\newcommand{\mathcal{D}}{\mathcal{D}}
\newcommand{\overset{rank}{=}}{\overset{rank}{=}}

\paragraph{Ranking by document likelihood}

The language modeling approach for information retrieval was originally
formulated as query-likelihood~\cite{Ponte98}. For our task, the document is the
``query'' for which we wish to rank chronons. We refer to this approach as
document-likelihood (DL).

We estimate $P(x|d) \propto P(d|x)P(x)$ via Bayes Rule. Assuming unigram
modeling, the likelihood of a test document $d$ is given by:

\begin{equation}
P(d|x) = \prod_{w \in d}\Theta^x_w
\end{equation}

\noindent
where the parameters of
$\Theta^x$ are estimated from the chronon $x$'s pseudo-document $d^x$, as described in
Section~\ref{s:smoothing}.

Just as informed document priors (e.g. PageRank or document length) inform
traditional document ranking in information retrieval, an informed prior over
chronons has potential to benefit our task as well. We adopt a chronon prior
intuitively informed by the distribution of training documents over chronons:
\begin{equation}
P(x) =
\frac{|d_{train} \in d^x|}{\sum_{\forall y} |d_{train} \in d^y|}
\label{eqn:nonUniformPrior}
\end{equation}
where $d_{train}$ is a training document, $d^x$ is the pseudo-document for
chronon $x$ and $|d_{train} \in d^x|$ is the number of dated training documents
overlapping with chronon $x$.

\paragraph{Ranking by model comparison} \label{sec:kl}

Zhai and Lafferty \shortcite{Lafferty01b} propose ranking via KL-divergence
between a query and each collection document.  Kumar et
al.~\shortcite{Kumar11-cikm} use this approach to compute $P(x|d)$, which is
estimated by computing the inverse KL-divergence of $x$ and $d$ and normalizing
this value with the sum of inverse divergences with all chronons $x_{1:n}$:

\begin{equation} \label{e:inverse}
P(x|d) = \frac{\mathcal{D}(\Theta^{d} || \Theta^{x})^{-1}}{\sum_{y\in x_{1:n}} \mathcal{D}(\Theta^{d} ||
\Theta^{y})^{-1}}
\end{equation}

\noindent
It is straighforward to see that their formulation is rank equivalent to
standard model comparison ranking with negative
KL-divergence~\cite{deJong05,Kanhabua08ecdl}:

\begin{equation} \label{e:req}
P(x|d)
\propto \mathcal{D}(\Theta^{d} || \Theta^{x})^{-1}
\overset{rank}{=} -\mathcal{D}_{KL}(\Theta^d ||\Theta^x)
\end{equation}

Lafferty and Zhai showed such ranking is equivalent to generating the query
(i.e.\ query-likelihood) assuming a uniform document prior and the query model
being estimated by relative frequency ~\cite{Lafferty01b}. This means that for
our task, if we adopt a uniform prior over chronons and estimate the document
model by relative frequency, then KL-ranking and document-likelihood approaches
will be rank equivalent.

\label{s:inference}

\paragraph{Prediction} Having determined $P(x|d)$, we choose the midpoint
$\hat{y}$ of the most likely chronon; for a chronon $x=[y, y+\delta]$, the
mid-point is $\hat{y} = y+\delta/2$.

\section{Related Work} \label{s:related}

{\bf Corpora for temporal evaluation.} With increased focus on temporal
analysis, there have been efforts to create richly annotated corpora to train
and evaluate temporal models, e.g. TimeBank \cite{timebank} and Wikiwars
\cite{Mazur:Dale:2010}
were created to
provide a common set of corpora for evaluating time-sensitive  models.
\shortcite{Loureiro11-GIS} use the above corpora to
resolve geographic and temporal references in text while
\shortcite{Chambers:Jurafsky:2008} use these to model event
structures.

{\bf Semantic based temporal models.} Time-sensitive models have also been
developed using semantic properties of data. \cite{Grishman:Huttunen:2002}
use semantic properties of web-data to create and automatically update a database
on infectious disease outbreaks. Other simpler approaches have been explored to
analyse literary and historical documents as well as recent datasets such as
tweets and search queries. Time based analysis of historical texts provides
important information as to how significant events happened in the past on a
temporal scale. The Google N-Grams
viewer\footnote{\url{http://ngrams.googlelabs.com/}}, which uses word counts
from millions of books and corresponding publication date, provides plots of
n-gram word sequences over a timeline \cite{GoogleN-Grams:2011}. This gives
useful insights into historical trends of events/topics and writing styles.
Time based analysis of tweets has gained popularity in recent years especially
to capture current trending topics for tracking news items and
market sentiment \cite{Zhang:Song:2010}.

{\bf Time aware latent models.} Another approach for temporal
text analysis is latent variable based graphical models. Dynamic Topic Models
\cite{Blei:Lafferty:2006} are used to analyze the evolution of topics over time
in a large document collection \cite{Blei:Heckerman:2008}.
\shortcite{Wang:McCallum:2006} analyse variations in topic
occurrences over a large corpora for a fixed time period.
\shortcite{Manning:Hall:2008} investigate the history of ideas in
a research field though latent variable approaches.
\shortcite{Chi:Zhu:2007} use graphical models for temporal analysis of
blogs and Zhang et al.\cite{Zhang:Song:2010} provide clustering techniques for
time varying text corpora through hierarchical Dirichlet processes for modeling time sensitivity.

{\bf Temporal analysis using conventional language models.} Time based
text analysis has been explored using conventional language model based
approaches for various applications e.g. time-sensitive query interpretation
\cite{Li03cikm,Dakka10}, time-based presentation of search
results~\cite{AlonsoCIKM09}, and modelling query and document changes over
time~\cite{Kulkarni11wsdm}. \cite{Li03cikm}, one of the early
temporal language models, use explicit document dates to estimate a more
informative document prior. More recently, \shortcite{Dakka10}
propose models for identifying important time intervals likely to be of interest
for a query incorporating document publication date into the ranking function.
\shortcite{AlonsoCIKM09}
use explicit
temporal metadata and expressions as attributes to cluster documents and create timelines
for exploring search results.

Document dating---the task of this paper---is a closely related problem.
~\shortcite{deJong05} follow a language model based approach to assign
dates to Dutch newspaper articles from 1999-2005 by partitioning the timeline
into discrete time periods.~\shortcite{Kanhabua08ecdl} extend
this work to incorporate temporal entropy and search statistics from Google
Zeitgeist. These approaches~\cite{deJong05,Kanhabua08ecdl} normalize the
evidence for each chronon by the whole collection.
~\shortcite{chambers:doctimestamps} improve over these by including
linguistic constraints such as NERs, POS tagging and regular expression
based temporal relation constraints (e.g. ``after'', ``before'' etc.) and using
MaxEnt classifier for training. ~\shortcite{Kanhabua:Romano:2012} use
linguistics features such as sentence length, context, entity list in a document
etc. to discover events over twitter and assign time stamp by framing it as a
binary classification problem with the two classes as relevant and non-relevant.
But, all these approaches worked for a small time range (6-10 years) but our datasets span
around 5000 years and the evidence would die down after normalization. ~\shortcite{Kumar11-cikm}
use divergence based methods and non-standard smoothing on Wikipedia biographies
for the same task.  We perform our
experiments on two of their datasets, Wikipedia biographies and Gutenberg short
stories, and we compare their smoothing method with  standard Jelinek-Mercer and
Dirichlet smoothing.

redpajama_set_name: RedPajamaArXiv


NASA is sending an $850 million Insight lander to Mars. Using a drill to dig deeper into the planet than ever before, it will be the first of its kind to study Mars' interior.
This mission will help us learn more about the origins of our solar system.


text:
Q: Recovering messages from rabbitmq queue in mule I am very much new to Mule ESB.
I have created a flow which has multiple queues(I am using RabbitMQ). The flow is something like some messages are put into first queue which will be read by second queue which will be read be third and so on.
Note: I am sending messages concurrently using JMeter.
Let's say before all message(s) can be put into third queue from second queue, my rabbitmq server is stopped. Now, in this case, I want to recover my messages. Also, I should be able to know what messages have been put into third queue and what are still left.
I might not have put my question in elegant or understandable way but i hope you understood what i want to achieve.

A: You can use Rollback Exception strategy (http://www.mulesoft.org/documentation/display/current/Rollback+Exception+Strategy) along with transactions: http://www.mulesoft.org/documentation/display/current/Transaction+Management when properly implemented messages that have not been delivered to the second queue will be rolled back automatically.
In rollback exception strategy you can write your custom behavior. Why don't you use rabbitmq client to see what messages where in third queue?

redpajama_set_name: RedPajamaStackExchange


text:
PURE NOSTALGIA
A private collection of historic vehicles
Dennis Lancet
RT buses
RF buses
About the RT family
RT1784 after completion of repaint in Spring 2002. The bus was restored to 1950's livery to participate in the Queen's Jubilee Tour 18/7/02. J Hinson
Some seven thousand buses of the RT family were built for London Transport between 1939 and 1954 creating the most standardised bus fleet in the world, although a number of design improvements and variations evolved as production progressed. The majority were finished in Central Area red livery, although many were painted green for Country Area and Green Line use.
Most were were based on the AEC Regent MkIII chassis built at Southall, being fitted with AEC 6-cylinder 9.6 litre engines. Transmission was through a four speed air operated pre-selective gearbox with fluid flywheel.
RT4275 emerges for the paint shop, a little dusty on top, 24/10/17 J Hinson
The majority were bodied by Park Royal Vehicles or Weymann.
The type proved immensely efficient and reliable, and some remained in public service with London Transport until as late as 1979.
Details of the vehicles: .
. .RT1784 . . . RT4275

redpajama_set_name: RedPajamaCommonCrawl


If mankind is to profit freely from the small and sporadic crop of the heroically gifted it produces, it will have to cultivate the delicate art of handling ideas. Psychology is now able to tell us with reasonable assurance that the most influential obstacle to freedom of thought and to new ideas is fear; and fear which can with inimitable art disguise itself as caution, or sanity, or reasoned skepticism, or on occasion even as courage.
'The Commemoration of Great Men', Hunterian Oration, Royal College of Surgeons (15 Feb 1952) British Medical Journal (20 Feb 1932), 1, 317-20. The Collected Papers of Wilfred Trotter, FRS (1941), 30.
Organic life, we are told, has developed gradually from the protozoan to the philosopher, and this development, we are assured, is indubitably an advance. Unfortunately it is the philosopher, not the protozoon, who gives us this assurance.
From Herbert Spencer lecture delivered at Oxford (1914) 'On Scientific Method in Philosophy', collected in Mysticism and Logic and Other Essays (1919), 106.
The inherent unpredictability of future scientific developments—the fact that no secure inference can be drawn from one state of science to another—has important implications for the issue of the limits of science. It means that present-day science cannot speak for future science: it is in principle impossible to make any secure inferences from the substance of science at one time about its substance at a significantly different time. The prospect of future scientific revolutions can never be precluded. We cannot say with unblinking confidence what sorts of resources and conceptions the science of the future will or will not use. Given that it is effectively impossible to predict the details of what future science will accomplish, it is no less impossible to predict in detail what future science will not accomplish. We can never confidently put this or that range of issues outside "the limits of science", because we cannot discern the shape and substance of future science with sufficient clarity to be able to say with any assurance what it can and cannot do. Any attempt to set "limits" to science—any advance specification of what science can and cannot do by way of handling problems and solving questions—is destined to come to grief.
The Limits of Science (1984), 102-3.
The primes are the raw material out of which we have to build arithmetic, and Euclid's theorem assures us that we have plenty of material for the task.
In A Mathematician's Apology (1940, 2012), 99.
To undertake a great work, and especially a work of a novel type, means carrying out an experiment. It means taking up a struggle with the forces of nature without the assurance of emerging as the victor of the first attack.
As quoted in Hans Straub and Erwin Rockwell (trans.), A History of Civil Engineering: An Outline From Ancient to Modern Times (1952), 157-158. Translated from Die Geschickte der Bauingenieurkunst (1949).
[The error in the teaching of mathematics is that] mathematics is expected either to be immediately attractive to students on its own merits or to be accepted by students solely on the basis of the teacher's assurance that it will be helpful in later life. [And yet,] mathematlcs is the key to understanding and mastering our physical, social and biological worlds.
In editorial in Focus, a Journal of the Mathematical Association of America (1986), quoted in obituary by Eric Pace, New York Times (11 Jun 1992).


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The Chalcedony Pact
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Post subject: The Chalcedony Pact
I'm just here to RP
"Woah woah woah. What about just signing a regular ...thing? You know what I mean, a treaty or something like that?"
In a small room stood the three remaining forest royals; a twenty four year old man with thick black hair that looked wild despite any attempts to tame it, an older man bearing a strong resemblance, and very frail old woman who sat knitting quietly. "....We're in no position for that sort of measure." The savage-looking king crossed his arms. "Familial ties are strong and there is no time."
"Dad. This isn't medieval times or whatever." His eyes were brown with golden hues. Motto of the Brook. He had a stocky build like his father; standing five feet and six inches tall with a powerful physique. Staggering back from a sudden rush of flames, Motto countered with an air-burst. Both men ceased when the tree-castle's ivy wound itself around them tight enough to prevent movement. "Motto." The old woman's tiny hand touched his. "This is our only chance to salvage what is left. The forest has already stopped talking to us....but it still speaks to you. Doesn't it?" The young man said nothing, but scowled and lowered his head. "Don't worry so much about whether or not she'll accept you."
"WHAT?" Motto had been released by the vines and stared incredulous at his grandmother. "Accept me?! I'm not worried about that. What the heck would you make you think that? Ha ha, that's crazy, Abe. Pshhh I'm fine. I got this." The two elders exchanged looks. "Good." His father grunted. "When the time and place is set, you will be there."
"Yeah." Motto stepped onto a branchy balcony. Beads of sweat were forming on his brow. "No problem."
Post subject: Re: The Chalcedony Pact
View Likes Posted: Tue Jul 31, 2018 1:18 am
SHE'S DEAD!
Location: the floor
Kudos on the Marriage!
You got yourself a looker!
He ain't the ugliest thing!
Ayy, stop by Lio's on Fifth, we got some gifts!
Light dimly stretched toward the windows of a room high above the city. Nothing save for the sound of the occasional mouse click filled the room as a young woman stared transfixed by her laptop. Her eyes scanned with burning focus as she looked at the emails and messages being sent to her by various family members. Her jaw had tightened and her hand tightly balled a fistful of her white silk sheets as she scrolled through the messages. Of course her Father wouldn't spend time sending little congratulations over this, he was the one setting it up after all and he knew she wouldn't be a fan.
A small, reluctant tap against the glass door of the patio and the woman's eyes darted upward. Her hand moved with blinding speed to shut the laptop, and slid it away. With a snap of her fingers the lamps on either side of bed eased into a warm orange light.
"un- ****ing believable!" she shouted down over the balcony as the figure slowly opened the glass door. It turned to gently close the door behind it before making it's way towards the stairs to the woman's massive bed.
"Actually, I should expect this from Ikathka Real himself. He thinks it's cool to just do.... this without asking me? You'd think-" her words caught in her throat as she watched the figure move.
The creature silently made it up the stairs before stiffly sitting at the foot of the bed. It opened a sharp-toothed mouth to speak before collapsing into cloud of oily black mist. When the mists had cleared, all that was left behind was a small defeated looking blackbird at the foot of her bed. All the rage and disgust that had been building in the girl dropped out of her in that instant.
"Jin, sweetie, It's okay," The woman said as she made her way to the foot of the bed "This is not your fault! You couldn't have known that Dad was going to do this,". Without waiting for a response, she scooped the small bird into her hands and brought it toward her chest. The little creature gave a small shudder before letting out a small noise; something between a sob and a chirp.
"I should've done more," his sweet small voice came out as a whisper "Your dad wouldn't have gone this far if I had just worked harder, made more progress, more territories, he would've finally trusted us, we could've told him. I-" another shudder and the boy was silent.
"Jin" the woman said with low even tone "I need you to look at me, Jin"
Despite the little bird's distress it did as it was told and peered up at the woman.
"Do I look angry at you, sweetie?" she cooed. The boy looked down and shook his head.
"No, Ma'am, Lady Ikathka, but I believe you should be,"
"No." She said sternly "This is Jota Ikathka's fault, and nothing you did was going to make him not be a pain in my ass." the anger that she had been containing bubbled up just for moment as she spat that name. She made her way back to the head of her bed and sat the bird down on a pillow "Now all we can do is fix this mess before it becomes a problem for us." she reopened the laptop and scrolled a bit to find an image. Oily black fog enveloped the bird and small black cat emerged to peer at the screen from the side. She brought up an image of an upbeat looking young man with sunny bright features and she tapped a manicured finger against the screen.
"You see this man?" she said as if she were speaking to a child "I need you to locate him and tell him something from me,"
The cat seemed transfixed by the man's image for a moment before swiveling his attention to his Lady "Yes, ma'am?" he squeaked.
The woman scratched the cat behind it's ear as she spoke eliciting a stream of soft purrs "Tell him, that his 'new Wife' would like to meet with him tomorrow morning at the Donna Cafe in Central Square mall. There are some things we need to talk about."
The cat stopped it's purring just long enough to respond "should I scare him a bit?"
The woman let out a small chuckle "I think you should! But not too badly, killing the boy might make things much worse for us,"
The moon was high in the sky by the time of his arrival. Jin beat large heavy wings as he made his way down to perch on the balcony of an Elemental Estate, being just loud enough to be heard by anyone in the adjacent room. He settled down before murky black tendrils enveloped him once more and a young man with piercing snake-eyes peered through the opening into a bedroom. Profane whispers filling the air around him as he reached his mind out toward the man he sought.
The Ikathka have a message for you.
That night Motto poured himself into pushups. He had successfully put off thinking about his situation for a long time now, easy to do when hidden away in the otherwise untouched wilderness. Over twenty years ago when s**t hit the fan with the Takers, the Elemental family retreated into the woods. Motto knew little else until his twelfth birthday when he embarked on his awakening; taking him all over the world. His magic was dangerously strong. He honed it and even dared to face off with a Taker...needless to say it didn't go well.
Despite the horrifying set-back, Motto's talent slowly returned after years in his forest castle. This whole marriage thing freaked him out for a bunch of reasons: The Takers were growing in number and getting ballsy. He was in legit danger and the confidence he had as a kid had never really come back. Plus holy s**t getting married. Sure he was a Prince but Motto was clueless when it came to formalities of any kind let alone royal stuff. And now he was to be wed with a Princess.
A shiver of excitement ran through and the raven-haired man paused in his exercises. Panting, he stared at the floor and imagined kissing a hot girl in a puffy dress with a tiara. Instead of reveling in the thought, Motto tensed and shut his eyes. That hot Princess needed actual protection and a dude who knew how to do royal stuff too. He chose to focus on protecting and upping his magic game.
A sudden shift in the room's atmosphere caused Motto's eyes to fly open. He wasn't alone. On his feet in an instant, the Elemental Prince took a defensive stance. There was a dude with friggin snake eyes just chillin'. Motto's already spiky hair stood on end as the ominous whispers filled his ears.
"Wait what?" Motto blinked and lowered his guard a little. "The Ikathka? The hell dude! You didn't have to come at me like that..what is it?" Irritated, the man relaxed and mopped the sweat off his face with a nearby tee-shirt. It occurred to him that this might be how the other kingdom rolled, and Motto's attitude brightened. "You..hungry or anything?"
Last edited by Gon Pro Hunter on Tue Jul 31, 2018 5:12 pm, edited 1 time in total.
View Likes Posted: Tue Jul 31, 2018 3:36 pm
Internally, Jin flinched, but his outward appearance reflected nothing. He wasn't taken aback by the man's words but by his presence. His stature wasn't anything but average and his appearance nothing of great note, but something about his.... being.
intense.
passionate.
strong.
Jin did all he could manage to shut his mind off to that presence, the whispers fading as he did so. He pulled a visible frown and took a step forward, his form easily towering over the man. He opened his mouth to speak but before he could manage any words the Prince spoke once more.
"You..hungry or anything?" he asked. It was as if he had a house guest and not a large winged devil at his door. That presence flooded toward Jin once more, warmer now. Pleasant even. Not the response he'd expected.
"N-no I- um, " his deep rumbling voice cracked for just a moment. Black tendrils, like ink twisting about in water cascaded off of Jin's body. Something like embarrassment flashed in the demon's features just for a moment and he took a step backward before he regained his composure.
"Lady Ikathka requests Motto of The Brook's presence at Donna Cafe in Central Square mall". He pointed an inky black clawed finger at the man, the whispers refilled the silence and intensified; a crescendo of voices increasing in urgency and sending tremors through the room. An image, a location, a time. All were placed directly into Motto's mind. The whispers continued, louder than screams as the flood of information was sent. It was deafening for just a moment and then. Silence. The creature placed his arm down, still blankly eyeing the man.
It would be unwise for Motto of the Brook to be late. The creature's lips did not move this time. It's gravelly, alien voice filled Motto's head and echoed loudly. Without waiting for a response, the creature slipped from the balcony and plummeted hard before launching into the air on large black feathered wings. Its body trailing those black wisps as it went.
A tiny blackbird fluttered down onto the penthouse patio and tapped a beak at the glass door before slipping in. It gave a small shake of its feathers before making its way toward the bottom of the stairs.
"You look guiltier than usual," the woman called down. The little bird started at the sound of her voice and slipped into cat form as it made its way up the stairs.
"How'd it go?" she inquired. She had still been deep in her messages but her focus had shifted to the small black cat.
"I-it went well! mhm, yup, message delivered, all good!" his small voice squeaked. He'd hopped onto the bed and taken seat at the foot of the bed.
"If you killed him, I need you to tell me, Jin," she said wearily
"He's not dead!" the boy nearly shouted, his ears flattened against his head and he looked away from the woman regretfully "He's just- I don't know, Ma'am. He's strange,"
"Most rich boys are weirdos," she said flatly, her gaze had returned to her laptop and she began typing something "Who needs to develop a personality when you've got money, right?" she added with a chuckle.
"Not like that, Ma'am" Jin said quietly "I couldn't concentrate when I got near him! It felt like he was... I don't know. It wasn't painful, just uncomfortable. I felt like I couldn't breathe! And he offered me food?" the little cat curled itself up before lying down "Even his sweat was strange! Can't get the scent of it out of my nose,". The flickering of his ears and thrashing of his tail were clear indications that he was pretty wound up about it all. The woman cracked a small smirk before closing her laptop and kicking the covers up.
"We can talk about it in the morning," she said, Jin could clearly hear that sly knowing tone in his lady's voice, and even if he wanted to know more, he wasn't going to press it.
"Good night ma'am,"
"Lady Ikathka requests Motto of The Brook's presence at Donna Cafe in Central Square mall".
Motto visibly crumbled before the dark creature as the frightening sensations overwhelmed him. Grunting, he covered his ears and inhaled a deep breath to expel into a defensive gust. Information came to his mind in a flash, astonishing the Elemental into withdrawing his attack. He'd never experienced magic like that before and it worried him. That snake eye dude was on a whole other level. Motto stood paralyzed in the thing's presence, wide-eyed and certain of his demise. It got into his mind.
It would be unwise for Motto of the Brook to be late.
Motto backed away, tripping over a book and falling onto his butt. With a panicked, boyish sound he put up an arm to protect himself but the threat was already gone. For several minutes Motto sat there breathing heavily with a hand clutching at his heart. That was straight up terrifying. With sudden grunt, he reached for a pen and scribbled on the nearest bit a paper: "Donna Cafe. Central..Square..Mall."
"S***.. what time?" Motto ran to his balcony and cupped his hands and yelled. "WHAT TIME??"
The Prince ran a shaking hand through his hair and grabbed a fresh tee-shirt. Stuffing his wallet into his back pocket, Motto dashed out of his chamber and out of the tree castle. He reached the Donna Cafe just before sunrise and let his back rest against the window while catching his breath. Eighty Kilometers. It was by no means the longest distance he'd ever covered in one go, but it was still enough to significantly wear him out. There was grime on his face and a bit of a scratch from a rock incident. His tee-shirt was sticky but he knew better than to take it off. Royal stuff to deal with. Had to be proper.. On time. ..
Motto slid to sit on the sidewalk and dozed off.
The woman sat cross-legged in the back seat and looked out of the darkened windows of her black car. Despite it being early morning, the sky was dark and there was a cold stiff breeze. Even with a tint on the windows, she could tell there was a storm in the air. People were still going about as always, but with much more urgency to get to their destination and out of the incoming bad weather. The woman picked up a small charcoal leather clutch from beside her and retrieved a tiny vial from a side pocket. The vial was filled entirely with a swirling black fluid. It trailed over itself in shiny rheoscopic swirls, like a small black tempest in a bottle, as she turned it over in her hand. She admired the patterns for just a while longer before the car came to a halt. Without prompting, she placed the vial back in her clutch, slipped the strap over her wrist and opened her door. The chauffeur stood hand outstretched to open the door with a defeated look on his wrinkled face, as if he were used to this. He sat back in his drivers seat with a sigh and a wipe at his brow.
"Still too slow," she said flatly as she stood out of the car and shut the door behind her "I might be a while so get lost for a while," she shouted back before making her way toward the cafe entrance. She stopped short of the entrance to see a grimy looking his majesty sleeping on the sidewalk. She looked blankly at the sad scene for a moment before turning to walk into the cafe. A smooth tone played as the door opened and the warm fragrance of coffee and spices wafted outward.
"Eyy! My little marfallina!" a small old man in a striped button up, green khaki shorts and brown sandals swiftly covered the floor with arms wide as he swooped in to hug the bride to be "I heard the good news, mija! Un marito real! Felices!" he chuckled and patted the girl on the back before moving to the side. He placed his hand up onto her shoulder and guided her toward the front, it took all she had not to scowl.
"Thank you, Jorge. Where is Donna?" she quickly redirected the conversation.
"Sai que she's in the back, mija," his loud voice cut through the all the noise in the cafe "Vai,mija! She's got something for you!"
"She makes me anymore cakes and I'm not gonna fit in a wedding dress," she called back as she made her way to the back room "Oh! and Jorge?" she turned on her heel and called back toward him " hay un ragazzo fuori. Traigalo al trasero?".
"wha?" the old man scratched a hand through his silvery head of hair before walking to the front to investigate. Sure enough, there was a sloppy passed out man right there. He scrunched his nose up at the scent and the image in general before running back in to get a pot.
SPLASH! a full pot of ice water was sent cascading over the slumped over man "Eyy!" the old man shouted "you stinkin' up my storefront! Go around back and take the stairs down."
Son of the Beast and the Leech | +
-King of the men that you truly fear most
-Quite a greedy guest, and not a gracious host
-Claiming souls for my father's land
-Preparing for war is my father's plan
-Revealing desires; dirty and unique
-Committing horrors mortals can't speak
-Ire to the man with a life full of hatred
-Blood from your veins, what you held most sacred.
-Sustain. Empower what you find unholy.
-Bleed. Feed who really needs you wholly.
-Salvation turned her back,
~Even when I sought her
- But Life is my wife and Death is her daughter
- Time goes by but I never grow old
- Happily,
-I watch your Skin. Turn. To Mold.
- Every time around another fleeting time of pleasure
-"Together.... we'll be-
Together-
Forever"
- but then you die, life fallen like a tiny feather
- just a bout of rain from a bad day of weather.
- Every time I feed I concede to my need............ -Unfinished
~Son of the Beast and the Leech
Everything stays
Right where you left it
but it still changes
Ever so Slightly
Daily and Nightly
In little ways
Posted: Wed Aug 01, 2018 11:17 pm
SPLASH! Motto jolted up and glared at the older man who looked responsible for the cold water.
"you stinkin' up my storefront! Go around back and take the stairs down."
Motto wasn't sure what to make of the instructions. Did the man send everyone that way or just dudes who accidentally fell asleep outside his cafe? His confusion was plain to see. Jorge's features stretched with agitation as he enunciated slowly for the culo, "She. is. waiting."
The younger man's eyes widened with sudden realization and he turned and ran. "S*** s*** s***." Motto muttered while clearing a stack of crates and squeezing past a startled baker. HE WAS LATE. "Stairs stairs." He located them and thundered down into the back room still dripping yet.
He yanked open a door to enter what looked like a nice little apartment and came to a halt. There was a woman sitting there reading and it was probably her house. Thinking he took the wrong set of stairs, Motto blurted an apology before shutting the door quickly and dashing back the way he came. A minute later, there was a soft knock at the door before the Elemental Prince opened it again.
As far as he could tell, no one was there besides the mocha-skinned woman. Squaring his shoulders, Motto turned to face her after shutting the door and strode to where she was. He stopped four feet from the lady and bowed at the waist. "Your Highness of Ikathka , I am Motto of the Brook. Heir to the Elemental Domain." Rising, a mild blush could now be seen on his face as well as a twitch of his jaw. Motto's hair was partially flattened against his head from the spontaneous ice bath and droplets of water continued to roll down his neck into the half drenched tee-shirt he wore. Somehow the grime from his journey remained; an awkward smear on his forehead and the scratch on his cheek. Although he governed his eyes reasonably well, Motto noted her clothes and figure. Her scent he hadn't fully made out yet, but it didn't matter much. She was hotter than he imagined except there was no tiara or pink stuff. "I am ..at your service.." He added in his best attempt at royal speak.
She had already seen him in pictures and videos. She'd already seen the disheveled state he'd been in at the front of the store. But something about watching him messily bumble about, rivulets of water dribbling from his head onto the floor, all caught her off guard. She took a moment to scan him over as he stiffly bowed and relayed information she already knew.
"Your Highness of Ikathka , I am Motto of the Brook. Heir to the Elemental Domain." he said as if he'd read it from a cue card before following it with a less rehearsed "I am ..at your service.."
Her eyes had returned to her book and she carefully marked her place before closing the book and placing it on the table in front of her. She uncrossed her legs and stood up to look at the man who was meant to be the solution to all of the territory struggles, stalemates, and corrupted governments. Even without the raised wedges of her ankle boots, she'd still be looking down at his, scratched, dirty, flushed face. The odor coming off the man mixed with her cherry blossom perfume into a hideous assault on the sense. Once the wave of nausea passed, rage bubbled in the pit of her stomach.
"Isabella's fine," she said coolly. Her voice was young and a touch low, more fitting for a girl who wears converse and checked flannel than a girl in macabre dark toned sweaters and scarves. She made a motion as if to outstretch a hand, but decided against it and instead pointed at a nearby closed door.
"The bathroom's over there and the room right there should have some spare clothes, we can talk once you've cleaned up," her words were professional and unemotional and, without waiting for a response, she made her way toward the stairs. She needed to cool off for a minute.
Motto considered himself decent at reading people, but the Ikathka Princess was a total mystery. Was is it just circumstances messing with him or was she reeeeeaally good at masking her intentions? Whatever the case was, she was taller. Dammit. Didn't matter though. Still super hot. Cherry blossoms were her thing apparently, but he was more interested in her hair.
"Isabella's fine."
"Oh." He was lame and it sucked.
His hand twitched to move and meet hers but it was feint! Dammit she was playing games with him. Motto's mouth fell open at the implied command to bathe and dress like a child or something. Isabella was already walking away.
"Sure thing." He wasn't amused. Unable to think of anything cool, Motto strode into the bathroom with his fists balled up. As expected, it was fancy and artsy in there. He undressed and stepped into the shower; his angered expression switching to confused. "HOW DOES THIS WOR--S***!" A little too fancy. Motto didn't see any way to start the water but he'd triggered it somehow. Fortunately for him, the water's temperature was ideal and his surprised melted into bliss. Turning, the raven let the pressured stream wash over his shoulders before rolling his head back to have his hair soaked.
Although his shower was brief, it was a luxurious one. Motto wanted to enjoy it longer but it felt weird and rude and it was freaking him out a little that he was supposed to marry that girl. He remembered to wear the towel around his waist before walking out and glanced around at the main area before heading into the second room Isabella pointed out. If there was nothing hindering him, the Prince would dress in the first pants he found and the white button down shirt seemed like a good idea. A jacket had been on the same hanger as the pants, but it was too formal. OR WAS IT? Motto hesitated before the mirror, but quickly shook his head and grabbed a pair of boots he assumed it was ok to borrow.
He didn't need the stinkin' jacket.
Refreshed and a little ticked off, Motto walked out into the main area and would continue up the stairs he'd seen her take if she wasn't waiting for him.
The door swung open and a red-haired slip of a woman carrying a massive tray of food shuffled quickly down the steps, almost barrelling into the man trying to come up them. Isabella followed close behind exchanging words with the woman in another language. The fiery-haired woman flitted her hand at the man to shoo him back down the steps, deftly balancing the monstrous tray in one hand for a moment as she descended down the steps.
"Now mija, I don't wanna hear any more of it," the woman's voice was loud and near scolding but somehow carried no malice "If it weren't for you, this place wouldn't even exist!" She placed the large tray on the living room coffee table and turned to face Isabella who'd been keeping pace closely behind her "you can keep whatever you want here: questa uomo aqui, gatos, enanos, cuantos demoni que vuole. Long as they don't come up into my kitchen, 'sta benne," she finished, snapping her gaze to the man with hard eyes before making her way back up the stairs.
Isabella wordlessly made her way to the table and set the television to the news and dropped the volume all the way down before making herself comfortable in an armchair directly facing the short edge of the coffee table. She leaned forward and unceremoniously grabbed a plump strawberry from the bowl of fruit. She took no time to consider it before biting it clean in half. She looked toward Motto as she chewed before motioning her hand toward the large tray. She chased the fruit with a gulp of water from a tall clear glass.
"Donna, always goes overboard with the food, help yourself" now that she had actually focused her attention on him, she could see that he cleaned up decently. Still looked like a kid in a summer suit but not too bad. His body filled out the clothes nicely, though he was a bit broad for the shirt. The outfit was a bit out of place for the weather today too. Images of thunderclouds and on site coverage of dark rolling clouds flashed on the screen for a while. Apparently the storm was going to be pretty big.
Motto looked up to see the duo and promptly back pedaled down the stairs. Out of his element and slightly intimidated, he stood a few paces back from the foot of the stairs and looked on as his bride-to-be descended. She moved with grace he decided. And her hair was absolutely rockin'. Motto inhaled the scent of it as she passed him by and wondered at his predicament. Was this actually happening and yikes he wasn't in her league at all. Then again, so what?
A pair of sharp eyes met with his and Motto snapped out of it. Whoever the red-headed woman was, she was intense and dammit she looked away just before he offered a proper smile. Motto turned his attention back to the Princess just as she plucked up a strawberry. Her relaxed manner was a welcome sight and the Elemental seated himself at the table's opposite end to face her. Motto ignored the television completely and helped himself to the entire wedge of brie; eating it in three bites and nodding with an appreciative grunt.
"So.." He was still chewing but Motto had swallowed enough for his words to be intelligible, "What did you want to talk about ?" A handful of whole strawberries went into his mouth next. He was almost always hungry as a result of his physical and magical traits. Motto's chewing slowed and his eyes flashed with uncertainty. "You did want to talk, ..right?"
She had a sneaking suspicion that the man would be a talking with his mouth full kind of guy. This she was okay with; not dignified and definitely not going to fit in at a formal party, but ravenous was a good quality. She was patient, sipping water and taking occasional bites of some sort of green wrap before wiping her mouth with a napkin and sitting up in her seat.
"It only makes sense for us to get to know each other, considering our parents decided we need to spend the rest of our lives together for the advancement of their plots," she rattled this off with a mock dismissive nature. A slip of irritation added a small edge to her voice that she hadn't meant to have. She could tell the man was already a bit intimidated by the situation and she pulled back the fire in her tone.
"Not that we'd make a bad looking couple, but an advantageous marriage isn't very romantic... especially when it isn't to my advantage" she chuckled and took a quick sip before standing up, leisurely walking over to the bar at the kitchenette and picking up her charcoal colored leather bag. She pulled a small vial filled with swirling black fluid from her bag and admired it for a moment.
"Tell me, Motto" her tone was kind enough but professional. An interrogation was about to take place "What have your parents told you about this situation?"
So she wanted to get to know him. Huh. He could deal with that. Motto relaxed even more and helped himself to several pastries that were calling his name. The sweet confections owned him for a moment but he stopped chewing at the trace of hostility in Isabella's tone. Sounded like she felt the same way about this whole wedlock thing.
The Princess's next words confused him; Motto wasn't sure if she was complimenting him or insulting him... or both. She wanted romance or something. That was understandable. Most girls did as far as he knew. But what the hell about not being to her advantage? It sounded snobby just like he expected..great.
"Tell me, Motto. What have your parents told you about this situation?"
He finished wiping his own mouth and continued to hold the napkin. "The usual. Our kingdom is fading, there aren't any guardians left, I'm the sole blah blah blah. It's being blown way out of proportion." It was clear that Motto didn't enjoy the topic, but he finished with an easy smile and assuring tone.
"Why? What are the Ikathka saying?" His head tilted with curiosity. The fact that she was playing around with a sketchy vial of black stuff didn't phase him. He'd seen plenty of weird stuff and this was totally chill.
Posted: Fri Aug 03, 2018 12:07 am
She could see red as the man spoke about the situation. There was burning rage in her gaze as her light brown eyes shifted from the vial to the man who just "blah blah'd" this situation. From what she could gather, his family was in as desperate situation as she expected to sign a pact with the Ikathka. She took a moment to remind herself that they were both being manipulated here and him not being aware of the gravity of the situation would probably make this marriage business easier on him.
"Maybe I should fill you in on a few things" she stated calmly "Word is that this pact and family merge are a bit more binding than I'd care for. My contacts have informed me of a blood geas that's been woven into the wording of the pact signing," She considered continuing but, with how clueless this kid was, she felt compelled to explain what this meant. She slowly strode over to him and delicately sat down on the large couch near his armchair "This spell is a powerful form of magic that compels the targets to do as directed unquestionably. Long story short, Jota Ikathka plans to make fodder of your territory, but that's just a small part of the spell. The Ikathka are a large family with countless footholds in various countries, and sometimes that big of a family can have insurgents. I'm going to guess that the vows at our wedding will bind us and our families more than just symbolically but in a way that makes conflicting interests a thing of the past. It would compel all Ikathka and it's associates to work toward the benefit of the family alone; it would make a literal puppet master out of Jota,"
She looked at a small scratch on Motto's face. It wasn't bleeding but it was a bit unsightly, without asking she reached to put a hand on his cheek and run a thumb over it. A small white crackle trailed over his face and the mark that had been there disappeared as if it had simply been wiped away. She smiled warmly, satisfied with her work, before grabbing a small slice of toasted ciabatta and taking a bite.
"Now, I don't know about you, but I'm not a fan of being a puppet. And, if you're interested, I think I might have a plan that would benefit both of us,"
Motto listened carefully as she re-joined him at the table.
"...magic that compels the targets to do as directed unquestionably.."
His eyes hardened. The possibilities of insurgents went completely over his head and the Prince didn't even hear the rest of Isabella's words. Compelled to do as directed. That was bad. Motto folded his hands and leaned his chin against them. Something needed to be done and soon. He wouldn't be made into a slave and who the heck would do that to their own daughter? The world was a darker place than he liked..all the more reason to stick to his forests and mountains. A light sensation on his cheek caused him to start and pull away. Before he could react, Motto's skin experienced a brief tenderness where she had touched him. A light gasp escaped his throat and she was smiling.
What was that all about? It sorta came out of nowhere.
Motto shifted to sit up a little taller and felt his tension return at the word "puppet."
"A plan? Mm." A firm nod. "Tell me." Motto was troubled by the new information and eager to escape his fate. The whole marriage thing just got ominous, but the Elemental heir was able to adapt quickly. Old magic was strong but not impossible to quell.
Before Motto could even finish speaking, Isabella uncapped the filled vial. The inky black fluid floated upward. Black snaking tendrils languidly made their way out and floated with intention toward the couch cushion next to Isabella. The tendrils coalesced into a thick cloud and began to take shape. A pair of golden cat eyes peered through the smoggy darkness. Its pupils dilate to paper thin slits as they pass over the Prince and his body takes form as a small black kitten. The kitten's tail bent and coiled slowly before it sat on its haunches and turned to look up at Isabella. Isabella had already busied her self with closing the vial back up.
"I believe you two have already met" Isabella's smile turned to a smirk at her comment. The small kitten popped up and bounced, pouncing forward playfully on the couch and looking back up the prince as if mocking him for his past fear.
"It's nice to see you again, Sir!" a bright little voice chirped out of the kitten "I-i'm sorry if I scared you too much last night," his voice didn't betray much remorse about his actions.
"He was slumped outside covered in dirt, Jin," Isabella added plainly "What time did you tell him to get here?"
"I said 8 o Clock! Like you told me!" the little kitten's ears perked and his tail flopped to the side as he turned to look at Isabella "Right?" he shifted to look at the Prince.
"Regardless, he's here now and he's agreed to help us out, Which makes this much easier" Isabella motioned from Jin to Motto and the kitten seemed to intuitively understand. He dropped down to the floor and bounded up the arm of Motto's seat before sitting back down and looking at the Prince with an excited expression on his face. His eye's pupils had widened into big black orbs.
"You've been kitnapped!" he chirped
"Kidnapped" Isabella corrected
"Right!" he added just as excitedly
"Considering how both sides of the pact believe they're the greater benefactors, it'll take a bit of time for either side to get suspicious of the other," she talked as she stood back up, made her way back over to her bag at the kitchenette table and placed the vial back in her bag. She turned her attention back toward Motto, crossing her arms and leaning back against the counter top as she did so "In fact, I have a few things planned to ensure that suspicion is shifted," she was looking at the screen. Coverage of a significant storm was taking place at the moment and something was running through her mind.
"For now, you can stay here, but later tonight, you and me have somewhere we need to go,"
Black swirling mist took to the air and Motto gripped the armchair. He was in trouble. The Prince rose quickly and leapt backward; placing himself between the chair and the snake eyed thing. Motto's movement was too fast for a normal person to discern, his agility wasn't entirely human after all.
"It's nice to see you again, Sir! I-i'm sorry if I scared you too much last night."
".....you.." Motto hadn't really formed a complete thought. He remained in his combat stance and blinked several times as the Princess addressed the kitten.
"I said 8 o Clock! Like you told me! Right?"
"Dude." Motto relaxed and scowled at the creature while returning to his seat.
"You've been kitnapped!"
"Kidnapped"
"Right!"
Motto's gaze fixed on the Princess while she explained her reasoning, his agitation became more and more noticeable until at last he got to his feet.
"For now, you can stay here, but later tonight, you and me have somewhere we need to go."
"Hold on. Just.. hold on a second. I get what you're saying. I do. But ...this is ...hardcore. Not that I have a problem with that but this could make things worse, Isabella." Motto moved to where she stood and faced her while resting his hands on his hips. He appeared to be thinking hard. "Instead of starting a war of our kingdoms, why not blame a common enemy?" Motto searched her eyes for signs of understanding. "You know who I'm talking about." If things went south with her plan, his people were in real danger.
For the first time in his life, the stakes were clear and Motto quaked inside himself at how vulnerable the Elementals had become. Rather than focus on the painful truth, he opted to keep things generalized.
"Listen, your plan isn't bad and I'm sure there's a lot more involved." He shifted his feet and ran a hand through his hair. "I'm grateful." The situation weighed heavily and Motto's face reflected it. "But Princess let's do this with the full consequences in mind, not just you and me escaping." He had more to say, but it could wait. Right now the engagement was sort of a big deal.
"oh he can think!" the kitten piped up before chuckling. Isabella was too surprised by the fact that he had actually been considering anything that she didn't even catch Jin's comment. Just for a moment she thought she might've underestimated Motto as some dimwitted kid. Even under the stress of the situation he was capable of picking up on her plot. Then he missed the target. Still, she was impressed that he'd come to the same conclusion as her. Maybe she should give him credit? It might do something to get him that much more into the plan. Motto had made his way over to her and was searching her gaze for some understanding. Isabella was sure he was trying to give her a knowing gaze, but his eyes were more intense and pleading.
She closed her eyes and let out a resigned sigh "fine, you're right," she lifted a phone to her face and started to scroll through her contacts "but the Ikathka's don't have clear cut enemies like your family may and us targeting your mortal enemy might look like a ploy," she placed her phone back in her back before turning to look at Motto again. Jin had silently made himself comfortable at Isabella's feet. Protective as always.
"And if the family we frame starts looking around and pointing fingers, we'll have three groups on our tail. Unless someone gets tipped off about where you've gone," she took a seat on one of the stools behind her and looked at Motto expectantly "So, pick a family, but pick wisely,"
"Wa- well.." Motto's poise faltered. She made a good point about being too obvious. Dammit. He wasn't good at this stuff. Frowning, he rubbed the back of his neck. "It doesn't feel right to choose. Innocent people could suffer…" A new idea came and he looked up with sudden clarity. "I'll do it. It's the only way." Stepping forward into the Princess's space, Motto's demeanor had completely changed. A confident smile full of serious intensity.
"I'm kidnapping you."
View Likes Posted: Sat Aug 04, 2018 2:52 pm
Isabella's eyes widened and her mouth opened as if to say something. Instead, a cold laugh escaped her lips. She didn't need to verify that it wasn't a joke, this boy had already showcased the extent of his critical thinking abilities and this seemed at about his level. "so let me get this straight," her tone was derisive " You don't want our family's to go to war right? Because here's what this sounds like: the Elementals have made a fool of Jota Ikathka by gaining his trust and then kidnapping his daughter in order to do God knows what, gain leverage? That's a war tactic,"
A pillar of Inky black tendrils climbed upward between the two of them and coalesced into the form of a slightly shorter but equally stocky raven haired boy with deep tan skin and eyes slanted nearly shut "hehe, 'scuse me" Jin said jovially. Despite the kind, cheery expression, his message and the physically force exuding from him was clear.
"Jin," Isabella started.
"Yes ma'am," Jin' voice was raspy and light, as if he were always whispering. His gaze never moved away from the man in front of him.
"How likely would the Wilds get involved in something like this?" she asked wearily. Still his gaze didn't move from the man, his body was like a smiling statue as he stood between them.
Little black ringlets of translucent mist trailed down the boy's body as he stood there in silence for a moment "only if contract holders or patrons were involved"
"Good to know," Isabella said slowly, her voice trailing off "That'll be all, Jin," without another word, the boy melted down into a small black cat and bounded back onto the arm of the couch.
"If perhaps you had been desperate enough to make a contract in the Wilds for some greater power, they could see this marriage as a conflict of interest, considering the power the geas would have over you, It wouldn't take much for a Demon or Fey to take your mind and have you try to capture me, the only issue is making that believable,"
"Ooh! ooh! I could-" Isabella shot Jin a look before he could even finish what he was saying "You could... find a Mystic Fey that requires some small quirk of him. Small." she said each word slowly as if she were warning the kitten. The kitten's head was low and his ears were pulled back.
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text:
Newark's Mean Lady plays nice at Firefly
When Katie Dill and Sam Nobles of Newark-based Mean Lady looked out at the crowd during their Firefly Music Festival performance, it was like an old episode of "This Is Your Life."
The sea of faces looking back at them were dotted with friends, family and a loud bunch of hardcore Delaware fans who roared Friday afternoon when Dill announced that the dream pop band was from The First State.
"We had a feeling a lot of people were coming just because it was Delaware, but looking out I saw elementary school, high school, work, the coffee shop -- people from our upbringing all in one place," Nobles said backstage after the well-received 45-minute set in front of nearly 1,000 festivalgoers.
Framed by the lush green forest behind them, the band's hypnotic dream pop was a perfect brunch set, kicking off at 1:30 p.m. under a striking sky blue sky that followed a Thursday full of clouds.
Mean Lady released its label debut last summer, "Love Now," through indie Mississippi-based Fat Possum Records. A follow-up album is already in the works.
Dill, wearing her trademark flower crown, delighted with her soulful, earthy vocals backed by Nobles on keyboards. Brian Bruce (drums) and Andrew Fusca (bass) of fellow stand-out Newark pop band FIANCÉ, rounded out the line-up for the high-profile festival gig.
Dill, who will stay in Dover to see Iron & Wine, Beck and others later this weekend, couldn't help but playfully fantasize about what could be next after her successful moment in the Firefly spotlight.
"We just need to keep climbing until we're jamming with them in the same room," Dill says. "We'd be like, 'Now I'm jamming with Beck in a kitchen at 3 in the morning!' This could be the first step toward that goal in life."
And at Firefly, it could happen.
The artist compound and lounge is a low-key hangout for the music acts to grab a drink and mingle, something that happens daily (and nightly) in The Woodlands.
Firefly gets a second shot of homegrown Delaware talent Saturday when Wilmington Americana/folk five-piece New Sweden brings a boatload of twang to the same Big Break Stage at 12:30 p.m.


Please note that this is a FREE course.
This course is part of the Business Transformation Programme and Personal Transformation Programme.
This course is part of the Business Transformation Programme.
This course is part of the Business Transformation Programme and Personal Transformation Programme, but it can be purchased as a standalone course.
This course is part of the Personal Transformation Programme, but it can be purchased as a standalone course.


A university in Scotland is hosting an oral health event designed to raise awareness of mouth cancer, which is on the rise in the UK and is now the country's sixth most common cancer.
As part of Mouth Cancer Awareness Week, the University of Dundee is set to host an event at which dental experts will be offering advice to members of the public on Monday afternoon (November 5th).
Awareness of mouth cancer is often low among members of the public, despite the fact that there are tens of thousands of new cases diagnosed in the UK every year.
"Early detection and treatment of the disease is vital. In addition we need to be raising the awareness of the risk factors and what people can do to help prevent the disease," said Mr Shepherd, who noted individuals should look at limiting the amount of alcohol they consume, as well as adopting a healthier diet and not smoking, in order to reduce their risk of developing the disease in the future.
Smoking and alcohol are the two main risk factors for mouth cancer, so those who drink to excess on a regular basis and also smoke are at a much higher risk of going on to develop the disease later in their lives than those who do not smoke or drink.
The university has also offered tips on how to spot oral cancer symptoms while the disease is in the early stages, while one of the signs to be on the lookout for is red or white patches.
Ulcers that do not heal within two weeks may be another sign of a presence of mouth cancer, while numbness of the tongue or other areas of the mouth is another symptom.
According to the NHS, oral cancers can develop in the salivary glands, tonsils and the part of the throat leading from your mouth to your windpipe.


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Karen Ledbury | Bio, Age, Net Worth (2021), Height, Relationship, Career |
Karen Ledbury is an Australian journalist, television personality and star on social media. She is known for her work in morning shows and commercials.
1 Why is Karen Ledbury famous?
2 How old is Karen Ledbury? Biology, citizenship, education
5 Rumours and Disputes
7 Karen Ledbury Relationship, boyfriend, married?
8 Social media : Twitter, Instagram
What is Karen Ledbury known for?
Australian journalist, broadcaster and social media star.
How old is Karen Ledbury? Biology, Citizenship, Education
Karen was born in Dalby, Queensland. In 2021, she'll be in her 30s. She's an Australian citizen. He is originally from Australia. Similarly, she did not disclose any details about her parents. She has a brother named Nicholas.
Signature: Karen Ledbury (source: auscelebsforums)
As for her education, Karen is a well-educated woman. She also belongs to a mixed ethnic group. He follows Christianity.
Karen is first and foremost a professional journalist and television personality. She is known for her work in morning shows and commercials. Ledbury also has a unique talent and interpersonal skills. She also works for various organizations such as Children's Charity, Wrestle at the Beaches, Save Our Son, and Diversity.
In addition to being a journalist, she is also a star on social media. Her charming personality and angelic looks attract many followers on her social media accounts.
If we talk about her income, she earns a decent amount with her journalism career and her presence on social media. His net worth is estimated at about $500,000. Similarly, Karen lives lavishly on her income.
Rumours and disputes
There are no rumors or controversies about them. She seems to be focusing on her career rather than getting bogged down in controversy.
How tall is Karen Ledbury? Karen is a beautiful girl with a lot of charm and personality. She is 1.80 m and weighs about 1.80 kg. But his body stats are 34-26-39. His hair is blond and his eyes are dark brown. And her cup size is 33C. She is also praised for her charming personality.
Relationship with Karen Ledbury, life partner, married?
Karen Ledbury in a relationship with an unknown man. So far, there's no information on this man. Her boyfriend, on the other hand, can be seen on several Instagram posts.
Signature: Karen Ledbury (Source: Twitter)
She met her boyfriend in college. Karen is also blessed with three sons.
Social media: Twitter, Instagram
Karen is very popular on social media. She has about 2.3K fans and 4K tweets on Twitter. His Instagram handle also has about 15.6 thousand followers.
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Local Wildlife Sites (LWS) are areas in Oxfordshire and Berkshire which include important and rare habitats and species. The 42,000 LWS in England (covering 5% of land) are essential in conserving wildlife in the UK and halting the loss of biodiversity.
LWS create a better connected landscape of wildlife buffers, corridors and stepping stones so that the countryside is more resilient to the pressures of modern living and climate change.
LWS are protected from harmful development through the planning system but as most sites are in private ownership, their long-term survival depends upon the interest and goodwill of their land managers and owners.
TVERC plays a key role in the survey, selection and maintenance of information on Local Wildlife Sites (previously known as Wildlife Heritage Sites in Berkshire and County Wildlife Sites in Oxfordshire). TVERC's approach to LWS identification, mapping & designation is consistent with the approach taken in other counties in England and in line with the DEFRA guidance on Local Sites. TVERC maintains a 'living list' of the Local Wildlife Sites in each local authority area in Berkshire and Oxfordshire, which is updated annually each May for the previous year.
Local authorities are required by central government to identify, designate and protect these sites through the planning system. TVERC carries out the identification and designation of Local Wildlife Sites on behalf of local authorities in Berkshire and Oxfordshire.
TVERC also reports annually to local authorities in Berkshire on how well LWS in their area are being managed. This information is used by local authorities in monitoring Local Plans, for corporate Biodiversity Action Plans and to report back to DEFRA on Single Data List requirement 160 "Proportion of Local Sites where positive conservation management is being achieved".
In Oxfordshire, this report is compiled by the Berkshire, Buckinghamshire & Oxfordshire Wildlife Trust.
Landowners and managers of Local Wildlife Sites may be able to access funding and advice on how best to manage their LWS.
In Oxfordshire, the Wildlife Sites Project officer based with the Berkshire, Buckinghamshire and Oxfordshire Wildlife Trust (BBOWT) can provide advice to landowners. Please see the BBOWT website for further information.
In Berkshire, landowners may be eligible to apply to Natural England for agri-environment funding to help maintain and enhance biodiversity on LWS. Please see the Natural England website for further guidance.
Landowners with woodlands can apply for support under Countryside Stewardship.
All landowners and managers can apply for TOE grants.
Survey work is carried out by TVERC staff and experienced volunteers, with the aim of surveying sites every 10 years. The information collected is used to assess sites against a range of criteria.
A site selection panel meets during the year to assess the results of the site surveys. The panel comprises representatives from TVERC, the local authorities, BBOWT, Natural England and local wildlife recorders. Panel decisions result in sites being designated as LWS (if they meet the criteria), de-selected (if they don't meet the criteria) or deferred (if further survey information is required). Sites remain designated as LWS and cannot be deselected until and unless sufficient evidence has been provided to demonstrate that they no longer meet the criteria. Landowners are made aware of these panel decisions.
Once any remaining issues about the decisions have been resolved, maps of the location of these sites are distributed to local authority planning staff (as well as other TVERC partners) to ensure they are taken into consideration in the planning process.


Damsel, a peregrine falcon, looks like she was giving us a piece of her mind yesterday at the SOAR raptor rescue facility. A fun outing for the Chicago group.
Copyright for this gallery photo belongs solely to Lindley Johnson. Images may not be copied, downloaded, or used in any way without the expressed, written permission of the photographer.