International audienceRelation extraction (RE) between a pair of entity mentions from text is an important and challenging task specially for open domain relations. Generally, relations are extracted based on the lexical and syntactical information at the sentence level. However, global information about known entities has not been explored yet for RE task. In this paper, we propose to extract a graph of entities from the overall corpus and to compute features on this graph that are able to capture some evidences of holding relationships between a pair of entities. The proposed features boost the RE performance significantly when these are combined with some linguistic features
Relation extraction is the task of ex-tracting predicate-argument relationships between entities fro...
Joint extraction of entities and relations is an important task in natural language processing (NLP)...
International audienceThe extraction and the disambiguation of knowledge guided by textual resources...
Knowledge Base Population (KBP) is an important and challenging task specially when it has to be don...
International audienceKnowledge Graphs (KG) offer easy-to-process information. An important issue to...
International audienceDuring the last decade, the need for reliable and massive Knowledge Graphs (KG...
Information Extraction (IE) aims at mapping texts into fixed structure representing the key informat...
The main purpose of the joint entity and relation extraction is to extract entities from unstructure...
Entity search is becoming a popular alternative for full text search. Recently Google released its e...
Document-level relation extraction aims to extract relations among multiple entity pairs from a docu...
We present an approach for extracting relations between named entities from natural language documen...
Sentence-level relation extraction (RE) aims at identifying the relationship between two entities in...
Recent years have seen a significant growth and increased usage of large-scale knowledge resources i...
ABSTRACT Recent works showed the trend of leveraging web-scaled structured semantic knowledge resour...
Abstract Document-level relation extraction is a challenging task in information extraction, as it i...
Relation extraction is the task of ex-tracting predicate-argument relationships between entities fro...
Joint extraction of entities and relations is an important task in natural language processing (NLP)...
International audienceThe extraction and the disambiguation of knowledge guided by textual resources...
Knowledge Base Population (KBP) is an important and challenging task specially when it has to be don...
International audienceKnowledge Graphs (KG) offer easy-to-process information. An important issue to...
International audienceDuring the last decade, the need for reliable and massive Knowledge Graphs (KG...
Information Extraction (IE) aims at mapping texts into fixed structure representing the key informat...
The main purpose of the joint entity and relation extraction is to extract entities from unstructure...
Entity search is becoming a popular alternative for full text search. Recently Google released its e...
Document-level relation extraction aims to extract relations among multiple entity pairs from a docu...
We present an approach for extracting relations between named entities from natural language documen...
Sentence-level relation extraction (RE) aims at identifying the relationship between two entities in...
Recent years have seen a significant growth and increased usage of large-scale knowledge resources i...
ABSTRACT Recent works showed the trend of leveraging web-scaled structured semantic knowledge resour...
Abstract Document-level relation extraction is a challenging task in information extraction, as it i...
Relation extraction is the task of ex-tracting predicate-argument relationships between entities fro...
Joint extraction of entities and relations is an important task in natural language processing (NLP)...
International audienceThe extraction and the disambiguation of knowledge guided by textual resources...