Datasets and methods for cross-document coreference resolution (CDCR) focus on events or entities with strict coreference relations. They lack, however, annotating and resolving coreference mentions with more abstract or loose relations that may occur when news articles report about controversial and polarized events. Bridging and loose coreference relations trigger associations that may lead to exposing news readers to bias by word choice and labeling. For example, coreferential mentions of “direct talks between U.S. President Donald Trump and Kim” such as “an extraordinary meeting following months of heated rhetoric” or “great chance to solve a world problem” form a more positive perception of this event. A step towards bringing ...
Event Coreference is an important module in the event extraction task, which has been shown to be d...
pre-printMost coreference resolvers rely heavily on string matching, syntactic properties, and seman...
Coreference resolution is the task of extracting referential expressions, or mentions, in text and c...
Datasets and methods for cross-document coreference resolution (CDCR) focus on events or entities w...
This paper presents a scheme for annotating coreference across news articles, extending beyond tradi...
Performing event and entity coreference resolution across documents vastly increases the number of c...
Cross-document coreference, the problem of resolving entity mentions across multi-document collectio...
Cross-document co-reference resolution (CDCR) is the task of identifying and linking mentions to ent...
Cross-sentence relation extraction deals with the extraction of relations beyond the sentence bounda...
posterCoreference resolution is the task of identifying coreferent expressions in text. Accurate c...
Event coreference resolution aims to determine and cluster event mentions that refer to the same rea...
We describe a scaffolding approach to the task of coreference resolution that incrementally combines...
Coreference resolution is one of the most fundamental Natural Language Processing tasks, aiming to i...
Journal ArticleWe aim to shed light on the state-of-the-art in NP coreference resolution by teasing...
State-of-the-art coreference resolutions systems depend on multiple LLM calls per document and are t...
Event Coreference is an important module in the event extraction task, which has been shown to be d...
pre-printMost coreference resolvers rely heavily on string matching, syntactic properties, and seman...
Coreference resolution is the task of extracting referential expressions, or mentions, in text and c...
Datasets and methods for cross-document coreference resolution (CDCR) focus on events or entities w...
This paper presents a scheme for annotating coreference across news articles, extending beyond tradi...
Performing event and entity coreference resolution across documents vastly increases the number of c...
Cross-document coreference, the problem of resolving entity mentions across multi-document collectio...
Cross-document co-reference resolution (CDCR) is the task of identifying and linking mentions to ent...
Cross-sentence relation extraction deals with the extraction of relations beyond the sentence bounda...
posterCoreference resolution is the task of identifying coreferent expressions in text. Accurate c...
Event coreference resolution aims to determine and cluster event mentions that refer to the same rea...
We describe a scaffolding approach to the task of coreference resolution that incrementally combines...
Coreference resolution is one of the most fundamental Natural Language Processing tasks, aiming to i...
Journal ArticleWe aim to shed light on the state-of-the-art in NP coreference resolution by teasing...
State-of-the-art coreference resolutions systems depend on multiple LLM calls per document and are t...
Event Coreference is an important module in the event extraction task, which has been shown to be d...
pre-printMost coreference resolvers rely heavily on string matching, syntactic properties, and seman...
Coreference resolution is the task of extracting referential expressions, or mentions, in text and c...