Challenge: In recent years, there has been a surge of interest in the natural language processing related to the real world . shogi commentaries are an interesting testbed for these tasks, but can be grounded in the game tree .
Approach: They propose to augment shogi commentaries with game states to generate a game commentary generator.
Outcome: The proposed system can be used to ground symbols and events with factuality . it can be compared with other systems to find out if a commentator is a human .

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Challenge: NLP studies have mostly dealt with factuality and modality separately . linguistic modality conveys the relationship a situation is supposed to have with respect to wishes, norms, goals, authority, etc.
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Constructing a Japanese Verdict Prediction Dataset for Fact-Checking of LLM-Generated Texts (2026.acl-srw)

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Challenge: Text generated by Large Language Models (LLMs) may contain plausible but incorrect information known as hallucinations.
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Event-Centric Natural Language Processing (2021.acl-tutorials)

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Challenge: This tutorial will provide an introduction to various methods for automating the extraction, conceptualization and prediction of events and their relations.
Approach: This tutorial will provide an introduction to various methods for automating events and their relations, and a wide range of NLU and commonsense understanding tasks.
Outcome: This tutorial will provide an introduction to various methods for automating extraction, conceptualization and prediction of events and their relations, and a wide range of NLU and commonsense understanding tasks.
Spanless Event Annotation for Corpus-Wide Complex Event Understanding (2024.lrec-main)

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Challenge: Existing methods for annotating multilingual, multimedia data are limited by the availability of multilingual corpora for schema-based event representation.
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Japanese Realistic Textual Entailment Corpus (2020.lrec-1)

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Challenge: a corpus of 48,000 realistic examples is the largest among publicly available Japanese TE corpora . a textual entailment corpus is used to train natural language understanding . authors: to be truly helpful, machines must understand the meaning of texts.
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Natural Language Annotations for Reasoning about Program Semantics (2023.findings-emnlp)

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Challenge: Xu et al., 2022) and Tafjord eet . al. 2021) have shown that programming assistants can explain their work by grounding natural language inference in code.
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The DReaM Corpus: A Multilingual Annotated Corpus of Grammars for the World’s Languages (2020.lrec-1)

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Challenge: Until recently, language descriptions were available in paper form only, with indexes as the only search aid.
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Corpus-Level Evaluation for Event QA: The IndiaPoliceEvents Corpus Covering the 2002 Gujarat Violence (2021.findings-acl)

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Challenge: a new corpus-level evaluation approach for event extraction is needed in social science applications . human annotations are often required to extract the actions of political actors and actors . a novel corpus evaluation approach can guide creation of similar social science-oriented resources .
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CAMERA³: An Evaluation Dataset for Controllable Ad Text Generation in Japanese (2024.lrec-main)

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Challenge: Despite numerous efforts in ad text generation, the aspect of diversifying a text has received limited attention, particularly in non-English languages like Japanese.
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The Possible, the Plausible, and the Desirable: Event-Based Modality Detection for Language Processing (2021.acl-long)

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Challenge: Existing studies restrict modal expressions to a closed syntactic class . modal sense labels are vastly different across different studies, lacking an accepted standard .
Approach: They propose a task where modal expressions can be words of any syntactic class and sense labels are drawn from a comprehensive taxonomy which harmonizes the modal concepts contributed by the different studies.
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