This paper describes a newly created text corpus of news articles that has been annotated for cross-document co-reference. Being able to robustly resolve references to entities across document boundaries will provide a useful capability for a variety of tasks, ranging from practical information retrieval applications to challenging research in information extraction and natural language understanding. This annotated corpus is intended to encourage the development of systems that can more accurately address this problem. A manual annotation tool was developed that allowed the complete corpus to be searched for likely co-referring entity mentions. This corpus of 257K words links mentions of co-referent people, locations and organizations (sub...
References included in multi-document summaries are often problematic. In this paper, we present a...
This article introduces a dialogue corpus containing data from two typologically different languages...
Abstract: We report on experiments for the Re-lated Entity Finding task in which we focus on only us...
Cross-document co-reference resolution (CDCR) is the task of identifying and linking mentions to ent...
Cross-document co-reference resolution (CDCR) is the task of identifying and linking mentions to ent...
This paper presents a scheme for annotating coreference across news articles, extending beyond tradi...
Cross-document co-reference resolution (CCR) computes equivalence classes over textual mentions deno...
We introduce a cross-document annotation toolset that serves as a corpus-wide knowledge base for lin...
Cross-document coreference, the problem of resolving entity mentions across multi-document collectio...
Identifying and linking named entities across information sources is the basis of knowledge acquisit...
This article introduces a dialogue corpus containing data from two typologically different languages...
Interpreting news requires identifying its con-stituent events. Events are complex linguis-tically a...
The intensive construction of domain-specific knowledge bases (DSKB) has posed an urgent demand for ...
We describe the practical details of a method for computing relations between co-occurring terms in ...
In this paper we present CROMER (CROss-document Main Events and entities Recognition), a novel tool ...
References included in multi-document summaries are often problematic. In this paper, we present a...
This article introduces a dialogue corpus containing data from two typologically different languages...
Abstract: We report on experiments for the Re-lated Entity Finding task in which we focus on only us...
Cross-document co-reference resolution (CDCR) is the task of identifying and linking mentions to ent...
Cross-document co-reference resolution (CDCR) is the task of identifying and linking mentions to ent...
This paper presents a scheme for annotating coreference across news articles, extending beyond tradi...
Cross-document co-reference resolution (CCR) computes equivalence classes over textual mentions deno...
We introduce a cross-document annotation toolset that serves as a corpus-wide knowledge base for lin...
Cross-document coreference, the problem of resolving entity mentions across multi-document collectio...
Identifying and linking named entities across information sources is the basis of knowledge acquisit...
This article introduces a dialogue corpus containing data from two typologically different languages...
Interpreting news requires identifying its con-stituent events. Events are complex linguis-tically a...
The intensive construction of domain-specific knowledge bases (DSKB) has posed an urgent demand for ...
We describe the practical details of a method for computing relations between co-occurring terms in ...
In this paper we present CROMER (CROss-document Main Events and entities Recognition), a novel tool ...
References included in multi-document summaries are often problematic. In this paper, we present a...
This article introduces a dialogue corpus containing data from two typologically different languages...
Abstract: We report on experiments for the Re-lated Entity Finding task in which we focus on only us...