| Challenge: | Frame shift is a cross-linguistic phenomenon in translation which results in corresponding pairs of linguistic material evoking different frames. |
| Approach: | They propose a task to predict cross-linguistic frame-to-frame correspondence and propose auxiliary training to learn cross-lingual frame-by-frame correlation. |
| Outcome: | The proposed task can learn cross-linguistic frame-to-frame correspondence and predict frame shifts in a Berkeley FrameNet-like configuration. |
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Frame Semantics across Languages: Towards a Multilingual FrameNet (C18-3)
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| Challenge: | This workshop will present current research on aligning Frame Semantic resources across languages . resources based on FrameNet have been created for roughly a dozen languages based upon Fillmore's Frame Sementics . |
| Approach: | This workshop will present current research on aligning Frame Semantic resources across languages . resources based on FrameNet have been created for roughly a dozen languages based upon Fillmore's Frame Sementics . |
| Outcome: | This workshop will present current research on aligning Frame Semantic resources across languages and automatic frame semantic parsing in English and other languages. |
Transfer of Frames from English FrameNet to Construct Chinese FrameNet: A Bilingual Corpus-Based Approach (L18-1)
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| Challenge: | Current publicly available Chinese FrameNet has a relatively low coverage of frames and lexical units compared with other languages. |
| Approach: | They propose an automatic way to construct Chinese FrameNet using a sentence-aligned English-Chinese bilingual corpus. |
| Outcome: | The proposed resource can provide frame recommendations acceptable by annotators. |
Cross-lingual Linking of Automatically Constructed Frames and FrameNet (2022.lrec-1)
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| Challenge: | Existing semantic frame resources have been manually elaborated, but manual development is labor-intensive. |
| Approach: | They propose to link Japanese frames to English FrameNet by using cross-lingual word embeddings and a model that takes only the frame-evoking words into account. |
| Outcome: | The proposed model will facilitate the development of cross-lingual frame resources. |
Do LLMs Encode Frame Semantics? Evidence from Frame Identification (2025.emnlp-main)
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| Challenge: | Using the FrameNet lexical resource, we evaluate large language models under prompt-based inference and observe that they can perform frame identification effectively even without explicit supervision. |
| Approach: | They evaluate large language models under prompt-based inference and observe that they encode latent knowledge of frame semantics. |
| Outcome: | The proposed model can generate coherent frame definitions while generalizing well to out-of-domain benchmarks. |
Diachronic word embeddings and semantic shifts: a survey (C18-1)
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| Challenge: | Existing methods for tracing time-related semantic shifts with word embedding models lack the cohesion, common terminology and shared practices of more established areas of natural language processing. |
| Approach: | They propose several axes along which these methods can be compared and propose a framework for comparison. |
| Outcome: | The proposed methods are compared with existing methods and outline their main challenges and potential applications. |
Fine-Grained Analysis of Cross-Linguistic Syntactic Divergences (2020.acl-main)
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Dmitry Nikolaev, Ofir Arviv, Taelin Karidi, Neta Kenneth, Veronika Mitnik, Lilja Maria Saeboe, Omri Abend
| Challenge: | Existing work on quantifying the prevalence of syntactic divergences across languages has not been done. |
| Approach: | They propose a framework for extracting divergence patterns for any language pair from a parallel corpus building on Universal Dependencies. |
| Outcome: | The proposed framework provides a detailed picture of cross-language divergences, generalizes previous approaches, and lends itself to full automation. |
A Danish FrameNet Lexicon and an Annotated Corpus Used for Training and Evaluating a Semantic Frame Classifier (L18-1)
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| Challenge: | a Danish FrameNet is a lexicon based on the Danish Thesaurus . it is significantly faster than building a new one from scratch . |
| Approach: | They propose a way to efficiently compile a Danish FrameNet based on the Danish Thesaurus . they present the corresponding corpus annotations of frames and roles and show how this can be used for a semantic frame classifier . |
| Outcome: | The proposed approach is faster than building a lexicon from scratch. |
Definition Generation for Automatically Induced Semantic Frame (2024.findings-acl)
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| Challenge: | Semantic frames are conceptual structures that describe specific types of situations or events. |
| Approach: | They propose to generate frame definitions from a set of frame-evoking words using a large language model. |
| Outcome: | The proposed task incorporates frame element reasoning as chain-of-thought to enhance the inclusion of correct frame elements in the generated definitions. |
Combining ELECTRA and Adaptive Graph Encoding for Frame Identification (2022.lrec-1)
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| Challenge: | Existing studies focus on FI tasks, but none have been done on the computational side. |
| Approach: | They propose a new system for Frame Identification based on pre-trained text encoders trained discriminatively and graphs embedding. |
| Outcome: | The proposed system produces state-of-the-art performance over two benchmarks and all possible splits and cleaning procedures used in the literature. |
Exploiting Definitions for Frame Identification (2021.eacl-main)
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| Challenge: | a frame-semantic parsing task is to determine which frame best captures the meaning of a word or phrase in a sentence. |
| Approach: | They propose a frame identification model that generates representations for frames and lexical units (senses) they evaluate the model on three data sets and show it consistently achieves better performance than previous systems. |
| Outcome: | The proposed model consistently outperforms previous systems on three data sets. |