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Datasets:
jsisonou
/
narrative-engine-emotion-7c

Tasks:
Text Classification
Sub-tasks:
sentiment-classification
Languages:
English
Size:
n<1K
Tags:
gated
research-only
non-commercial
schema-stable
reproducible
7c
License:
Dataset card Data Studio Files
xet
Community
Dataset Preview
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
The dataset generation failed because of a cast error
Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 1 new columns ({'label\tV_bin\tA_bin\tD_bin\tdirection'}) and 7 missing columns ({'scene_idx', 'conf', 'arousal', 'plot_break', 'dominance', 'label', 'valence'}).

This happened while the csv dataset builder was generating data using

hf://datasets/jsisonou/narrative-engine-emotion-7c/lexicon/core100.v1.bin.tsv (at revision fbc505ded01484cabc8c969ae38c994129a53f0e)

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1831, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 644, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              label	V_bin	A_bin	D_bin	direction: string
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 435
              to
              {'scene_idx': Value('int64'), 'valence': Value('float64'), 'arousal': Value('float64'), 'dominance': Value('float64'), 'label': Value('string'), 'conf': Value('float64'), 'plot_break': Value('float64')}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1456, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1055, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 894, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 970, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1702, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1833, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 1 new columns ({'label\tV_bin\tA_bin\tD_bin\tdirection'}) and 7 missing columns ({'scene_idx', 'conf', 'arousal', 'plot_break', 'dominance', 'label', 'valence'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/jsisonou/narrative-engine-emotion-7c/lexicon/core100.v1.bin.tsv (at revision fbc505ded01484cabc8c969ae38c994129a53f0e)
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

scene_idx
int64
valence
float64
arousal
float64
dominance
float64
label
string
conf
float64
plot_break
float64
1
0.75
0.6
0.9
pride
1
0
2
0.2
0.925
0.5
anger
0.705492
1
3
0.43
0.83
0.41
astonishment
0.586948
0
4
0.388
0.75
0.312
nervousness
0.579233
1
5
0.175
0.783
0.333
tension
0.789985
1
6
0.2
0.9
0.3
fear
1
0
7
0.63
0.61
0.46
longing
0.854314
0
8
0.3
0.6
0.3
worry
1
0
9
0.5
0.5
0.5
longing
0.595939
1
1
0.3
0.6
0.3
worry
1
0
2
0.2
0.95
0.4
anger
1
0
3
0.4
0.5
0.3
confusion
1
0
4
0.425
0.9
0.525
astonishment
0.583503
0
5
0.75
0.675
0.55
fascination
0.785714
1
6
0.5
0.5
0.5
longing
0.595939
1
7
0.9
0.5
0.8
compassion
1
1
8
0.9
0.5
0.733
grateful
0.905714
0
1
0.5
0.5
0.5
longing
0.595939
1
2
0.7
0.6
0.6
interest
1
0
3
0.2
0.8
0.4
tension
1
0
4
0.7
0.6
0.6
interest
1
0
5
0.45
0.875
0.35
astonishment
0.589674
0
1
0.8
0.5
0.6
hope
1
0
2
0.225
0.825
0.45
tension
0.825036
0
3
0.2
0.95
0.2
shock
1
0
4
0.77
0.58
0.5
sympathy
0.764394
0
5
0.5
0.5
0.5
longing
0.595939
1
6
0.5
0.5
0.5
longing
0.595939
1
7
0.183
0.5
0.333
disappointment
0.893939
1
8
0.1
0.4
0.2
sorrow
1
0
1
0.5
0.5
0.5
longing
0.595939
1
2
0.5
0.5
0.5
longing
0.595939
1
3
0.5
0.5
0.5
longing
0.595939
1
4
0.1
0.8
0.45
tension
0.680562
0
5
0.5
0.5
0.5
longing
0.595939
1
6
0.3
0.6
0.5
annoyed
1
0
7
0.7
0.6
0.6
interest
1
0
8
0.5
0.5
0.5
longing
0.595939
1
9
0.9
0.6
0.6
amusement
1
0
10
0.3
0.6
0.3
worry
1
0
11
0.15
0.7
0.6
resentment
1
0
12
0.183
0.883
0.283
fear
0.915872
0
13
0.3
0.6
0.5
annoyed
1
0
14
0.85
0.4
0.7
relief
1
0
1
0.5
0.5
0.5
longing
0.595939
1
2
0.5
0.5
0.5
longing
0.595939
1
3
0.55
0.95
0.6
astonishment
0.548246
0
4
0.2
0.95
0.4
anger
1
0
5
0.05
0.7
0.1
despair
1
0
1
0.3
0.6
0.3
worry
1
0
2
0.5
0.5
0.5
longing
0.595939
1
3
0.6
0.55
0.45
longing
0.797969
0
4
0.5
0.5
0.5
longing
0.595939
1
5
0.75
0.6
0.7
curiosity
1
0
6
0.2
0.9
0.3
fear
1
0
1
0.483
0.667
0.433
longing
0.569841
0
2
0.54
0.66
0.54
longing
0.731976
0
3
0.45
0.6
0.55
irritation
0.714286
0
4
0.443
0.736
0.464
impatience
0.587531
0
5
0.225
0.65
0.4
envy
0.785714
0
6
0.15
0.5
0.3
hurt
1
0
7
0.75
0.525
0.75
curiosity
0.742461
0
8
0.693
0.607
0.543
interest
0.834705
0
9
0.664
0.529
0.486
sympathy
0.737625
1
10
0.3
0.6
0.3
worry
1
0
1
0.35
0.6
0.55
irritation
1
0
2
0.662
0.475
0.562
absorption
0.71697
0
3
0.65
0.5
0.6
absorption
0.714286
0
4
0.167
0.9
0.333
fear
0.86666
0
5
0.45
0.6
0.55
irritation
0.714286
0
6
0.55
0.55
0.5
longing
0.797969
0
7
0.183
0.667
0.467
bitterness
0.781153
1
8
0.5
0.5
0.5
longing
0.595939
1
1
0.5
0.5
0.5
longing
0.595939
1
2
0.35
0.731
0.537
impatience
0.708208
1
3
0.375
0.95
0.45
anger
0.479992
1
4
0.51
0.72
0.64
anticipation
0.442308
1
5
0.4
0.595
0.485
irritation
0.765262
0
6
0.267
0.6
0.283
worry
0.893939
0
7
0.5
0.5
0.5
longing
0.595939
1
1
0.542
0.621
0.537
longing
0.794484
0
2
0.75
0.49
0.7
trust
0.712861
1
3
0.393
0.729
0.407
impatience
0.701172
0
4
0.588
0.525
0.55
longing
0.740188
1
1
0.2
0.5
0.325
disappointment
0.928571
0
2
0.25
0.8
0.3
nervousness
1
0
3
0.328
0.694
0.406
envy
0.850007
0
4
0.5
0.5
0.5
longing
0.595939
1
5
0.3
0.6
0.3
worry
1
0
1
0.5
0.5
0.5
longing
0.595939
1
2
0.2
0.586
0.307
guilt
0.955279
0
3
0.45
0.533
0.433
confusion
0.583229
1
4
0.5
0.5
0.5
longing
0.595939
1
5
0.7
0.512
0.637
absorption
0.819005
0
1
0.65
0.5
0.6
absorption
0.714286
0
2
0.213
0.675
0.425
jealousy
0.77109
1
3
0.2
0.95
0.4
anger
1
0
4
0.483
0.533
0.383
confusion
0.651628
0
1
0.2
0.8
0.4
tension
1
0
2
0.35
0.6
0.45
annoyed
0.797969
0
End of preview.

Latest: v1_0 · vol01 · ep001 — 7c updated (N scenes). No-fee • Research-only • Access request required.

No-fee (access request). Research-only. Includes 5c columns plus conf and plot_break. For a public sample, see the 5c Research Pack.

This is the 7c Core Stable edition (Free, Gated) under the JsisOn License (ARR). It contains the emotion curve only (CSV) with the same 7 fields across releases; schema-stable and reproducible. For open exploration see 5c Free; for richer yet stable coverage, 15c Extended (superset).

Anchor Non-Disclosure (ARR)
This edition does not include numeric lexicon anchors. Per-scene VAD values are pre-snap continuous estimates, not label anchor coordinates.

Why 7c (vs 9c)

  • Fixed 7 columns, zero-NA policy, range-checked → downstream-stable.
  • Internal thresholds/distances are not exposed → IP-safe.
  • Curve-only CSV; no JSONL scenes or full text.
  • Fixed lexicon version (JS-LEX core100 v1) → stable labels across releases.
  • Labels use stable identifiers; the mapping is provided in lexicon/core100.v1.bin.tsv.

Schema (7 columns)

scene_idx | valence | arousal | dominance | label | conf | plot_break

Sample (CSV)

scene_idx,valence,arousal,dominance,label,conf,plot_break 1,0.5,0.5,0.5,longing,0.595939,1 2,0.7,0.6,0.6,interest,1,0 3,0.2,0.8,0.4,tension,1,0 4,0.7,0.6,0.6,interest,1,0 5,0.45,0.875,0.35,astonishment,0.589674,0

  • Fields

    • scene_idx (int) — 1-based index within the episode
    • label (string) — primary emotion from JS-LEX core100 v1 (see lexicon/core100.v1.bin.tsv)
    • conf (float, 0..1) — confidence for label
    • valence (float, 0..1)
    • arousal (float, 0..1)
    • dominance (float, 0..1)
    • plot_break (boolean: 0/1)

Files

  • data/7c_curve.csv — per-scene emotion curve (7 cols)
  • schema/public_contract.schema.json — public interface (no implementation details)
  • docs/LICENSE.txt — JsisOn License (ARR) terms
  • docs/GATED_POLICY.md — access terms
  • lexicon/core100.v1.bin.tsv

Lexicon (core100.v1)

  • We provide a minimal, non-numeric VAD lexicon to ensure reproducibility without exposing raw anchors.
  • File: lexicon/core100.v1.bin.tsv (UTF-8, TSV)
  • Columns: label, V_bin, A_bin, D_bin, direction
  • Bins: VL, L, M, H, VH (five ordered levels around the neutral anchor)
  • Neutral anchor: conceptually (0.5, 0.5, 0.5) — choose midpoints per your protocol.
  • Version: core100.v1
  • License: research-only (no redistribution / no training without consent)
  • Exact numeric anchors are reserved to the Pro edition;
  • attempts to reconstruct anchors are not permitted under ARR.

Reconstruction (optional, by user)
Researchers may map bins to numeric midpoints (e.g., a 5-level scale) in their own code/protocol to derive approximate VAD values for analysis. This dataset intentionally does not include numeric coordinates.

Dataset Summary

7-column VAD core for research and prototyping. No source text. Derived from Batalstone vol.1 pipeline ([email protected], JS-LEX core100).

Access & Gating

This is a Gated Free dataset under the JsisOn License (ARR).

  • Allowed (non-commercial only): academic research, evaluation, and model training for research.
  • Prohibited: commercial training/deployment, resale, sublicensing, redistribution.
    Access is free after approval on the Hub (request access and accept ARR terms).

Data Structure 

.
├─ data/
│  └─ 7c_curve.csv          
├─ schema/
│  └─ public_contract.schema.json  
├─ lexicon/
│  └─ core100.v1.bin.tsv     
├─ docs/
│  ├─ LICENSE.txt           
│  └─ GATED_POLICY.md
  • VAD fields are pre-snap continuous estimates;
  • numeric lexicon anchors are not part of this edition.

B. Schema (public)

schema/public_contract.schema.json

{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "$id": "https://schemas.jsison.com/batalstone/curve_7c_core.arr.v1.json",
  "title": "Batalstone 7c Core Stable — Curve Only (ARR)",
  "description": "No numeric lexicon anchors are included; VAD fields are pre-snap continuous estimates.",
  "type": "object",
  "required": ["scene_idx","valence","arousal","dominance","label","conf","plot_break"],
  "properties": {
    "scene_idx": { "type": "integer", "minimum": 1, "description": "1-based scene index" },
    "valence":   { "type": "number",  "minimum": 0.0, "maximum": 1.0 },
    "arousal":   { "type": "number",  "minimum": 0.0, "maximum": 1.0 },
    "dominance": { "type": "number",  "minimum": 0.0, "maximum": 1.0 },
    "label":     {
      "type": "string",
      "description": "Primary emotion (JS-LEX core100 v1). See lexicon/core100.v1.bin.tsv (non-numeric bins)."
    },
    "conf":      { "type": "number",  "minimum": 0.0, "maximum": 1.0 },
    "plot_break":{
      "description": "0/1 in CSV; cast to boolean by readers",
      "oneOf":[{"type":"integer","enum":[0,1]},{"type":"boolean"}]
    }
  },
  "additionalProperties": false
}

from datasets import load_dataset, Features, Value
features = Features({
  "scene_idx": Value("int32"),
  "valence":   Value("float32"),
  "arousal":   Value("float32"),
  "dominance": Value("float32"),
  "label":     Value("string"),
  "conf":      Value("float32"),
  "plot_break":Value("bool"),
})
ds = load_dataset("jsisonou/webnovel-narrative-emotion",
                  data_files="data/7c_curve.csv",
                  split="train",
                  features=features)
Edition Columns Access Purpose Why choose it
9c Preview (archived) 9 + diagnostics archived historical preview experimental fields; unstable
7c Core (gated, free) 7 gated-free (ARR) research & evaluation standard stable schema, zero-NA, fixed lexicon, reproducible
5c Free 5 public quick baselines ultra-light, open

Intended Use & Limitations

Research, benchmarking, prototyping. Non-commercial model training and evaluation are allowed; any commercial use requires a separate written agreement (see License).

License

LicenseRef-JsisOn (ARR) — full text in docs/LICENSE.txt.
Summary: https://js-is-on.com/licenses/1.0/
(Non-commercial research/review only; no redistribution, sublicensing, or commercial training/deployment.)

Contact: [email protected] → 5c Research Pack

Changelog

1.0.0 — Initial 7c Core Stable (no-TH). Supersedes legacy 9c preview.

@dataset{batalstone_emotion_7c_core_arr_2025, author = {Liia Black}, title = {Webnovel Narrative Emotion — 7c Core Stable (Gated, Free)}, year = {2025}, publisher = {JsisOn OÜ} }

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