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pro vyhledávání: '"Ahmed, Shafiuddin Rehan"'
Generating Harder Cross-document Event Coreference Resolution Datasets using Metaphoric Paraphrasing
Autor:
Ahmed, Shafiuddin Rehan, Wang, Zhiyong Eric, Baker, George Arthur, Stowe, Kevin, Martin, James H.
The most popular Cross-Document Event Coreference Resolution (CDEC) datasets fail to convey the true difficulty of the task, due to the lack of lexical diversity between coreferring event triggers (words or phrases that refer to an event). Furthermor
Externí odkaz:
http://arxiv.org/abs/2407.11988
Autor:
Nath, Abhijnan, Jamil, Huma, Ahmed, Shafiuddin Rehan, Baker, George, Ghosh, Rahul, Martin, James H., Blanchard, Nathaniel, Krishnaswamy, Nikhil
Event coreference resolution (ECR) is the task of determining whether distinct mentions of events within a multi-document corpus are actually linked to the same underlying occurrence. Images of the events can help facilitate resolution when language
Externí odkaz:
http://arxiv.org/abs/2404.08949
Autor:
Ahmed, Shafiuddin Rehan, Baker, George Arthur, Judge, Evi, Regan, Michael, Wright-Bettner, Kristin, Palmer, Martha, Martin, James H.
Event Coreference Resolution (ECR) as a pairwise mention classification task is expensive both for automated systems and manual annotations. The task's quadratic difficulty is exacerbated when using Large Language Models (LLMs), making prompt enginee
Externí odkaz:
http://arxiv.org/abs/2404.08656
This paper presents a novel Cross-document Abstract Meaning Representation (X-AMR) annotation tool designed for annotating key corpus-level event semantics. Leveraging machine assistance through the Prodigy Annotation Tool, we enhance the user experi
Externí odkaz:
http://arxiv.org/abs/2403.15407
Autor:
Cai, Jon Z., Ahmed, Shafiuddin Rehan, Bonn, Julia, Wright-Bettner, Kristin, Palmer, Martha, Martin, James H.
In this paper, we introduce CAMRA (Copilot for AMR Annotatations), a cutting-edge web-based tool designed for constructing Abstract Meaning Representation (AMR) from natural language text. CAMRA offers a novel approach to deep lexical semantics annot
Externí odkaz:
http://arxiv.org/abs/2311.10928
Autor:
Ahmed, Shafiuddin Rehan, Nath, Abhijnan, Regan, Michael, Pollins, Adam, Krishnaswamy, Nikhil, Martin, James H.
Annotating cross-document event coreference links is a time-consuming and cognitively demanding task that can compromise annotation quality and efficiency. To address this, we propose a model-in-the-loop annotation approach for event coreference reso
Externí odkaz:
http://arxiv.org/abs/2306.05434
Event Coreference Resolution (ECR) is the task of linking mentions of the same event either within or across documents. Most mention pairs are not coreferent, yet many that are coreferent can be identified through simple techniques such as lemma matc
Externí odkaz:
http://arxiv.org/abs/2305.05672
Event coreference continues to be a challenging problem in information extraction. With the absence of any external knowledge bases for events, coreference becomes a clustering task that relies on effective representations of the context in which eve
Externí odkaz:
http://arxiv.org/abs/2102.09600
In this paper, we propose a pipeline to convert grade school level algebraic word problem into program of a formal languageA-IMP. Using natural language processing tools, we break the problem into sentence fragments which can then be reduced to funct
Externí odkaz:
http://arxiv.org/abs/2003.11517