Frame Semantics across Languages: Towards a Multilingual FrameNet
FrameNet is a lexical resource that provides rich semantic representations of the core English vocabulary based on Fillmore's Frame Semantics, with more than 200k manually annotated examples. Resources based on FrameNet have now been created for roughly a dozen languages. This workshop will present current research on aligning Frame Semantic resources across languages and automatic frame semantic parsing in English and other languages. We will explore the extent to which semantic frames are similar across languages and the implications for theories of semantic universals, the practice of translation (whether human or machine) and multilingual knowledge representation. Does not require prior familiarity with Frame Semantics. 1 Description The FrameNet Project at the International Computer Science Institute (ICSI, http:/framenet. icsi.berkeley.edu) has created a detailed lexical database of contemporary English, (currently more than 13,000 lexical units in 1,200 semantic frames) based on Frame Semantics (Fillmore (1977) (1985) NLP researchers have shown that such representations are useful in diverse applications such as question answering, text to scene systems, dialog systems, and social network extraction. Separate research projects have now developed Frame Semantic lexical databases for roughly a dozen languages (including Brazilian Portuguese, Chinese, Hebrew, Japanese, Korean, and Swedish) based in varying degrees on the original FrameNet structure, methodology and annotation practices (Ruppenhofer et al. 2016) Most have taken the ICSI English frames as a starting point and have found that the majority of target language words fit comfortably in those frames. The FrameNet team is developing alignments across these FrameNets, seeking to understand crosslinguistic similarities and differences in framing. Going beyond alignments between frames, we also use techniques such as multilingual word vectors (Hermann and Blunsom, 2014) to cluster and align lexical units (each a single sense of a word in a frame) across languages. The underlying research questions include: To what extent are semantic frames the same cross culturally and cross linguistically? Where they differ, what are the reasons for these differences? Will translations to be "frame preserving" This tutorial will discuss the methodology and status of the alignment effort, and of a recently launched parallel manual annotation task, and theoretical issues that have emerged in this area of research, including the interplay between semantic frames and constructions in different languages. We will also report on the state of the art in automatic frame semantic role labeling for English (Swayamdipta et al. 2017) and for other languages. This can be regarded as a structured prediction task which maps a sentence to a graph with nodes for each predicator and its arguments and adjuncts, linked by arcs representing the frame semantic roles. Recent approaches rely on neural architectures to learn representations which enforce global consistency for each classification decision and can learn from disparate data. Participants in this tutorial will learn about: 1. Multilingual FrameNet, its methodology and practices 2. Cross linguistic similarities and differences among the languages
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