Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Kiril Gashteovski"'
Autor:
Bhushan Kotnis, Kiril Gashteovski, Daniel Rubio, Ammar Shaker, Vanesa Rodriguez-Tembras, Makoto Takamoto, Mathias Niepert, Carolin Lawrence
Open Information Extraction (OpenIE) is the task of extracting (subject, predicate, object) triples from natural language sentences. Current OpenIE systems extract all triple slots independently. In contrast, we explore the hypothesis that it may be
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2f8b38acc56ed83367905b5373960fa3
Publikováno v:
Proceedings of the First Workshop on Evaluation and Comparison of NLP Systems.
Open information extraction (OIE) is the task of extracting relations and their corresponding arguments from a natural language text in un- supervised manner. Outputs of such systems are used for downstream tasks such as ques- tion answering and auto
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f8196f84598d241582c7d4cc7b1e9d2a
https://doi.org/10.18653/v1/2020.eval4nlp-1.14
https://doi.org/10.18653/v1/2020.eval4nlp-1.14
Publikováno v:
ACL
MADOC-University of Mannheim
MADOC-University of Mannheim
Open Information Extraction systems extract (“subject text”, “relation text”, “object text”) triples from raw text. Some triples are textual versions of facts, i.e., non-canonicalized mentions of entities and relations. In this paper, we
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e9726500d91e88ebd73353952b1de9e9
https://doi.org/10.18653/v1/2020.acl-main.209
https://doi.org/10.18653/v1/2020.acl-main.209
Publikováno v:
JCDL
We present a toolkit and dataset for entity-aspect linking. The tool takes as input a sentence and provides the most relevant aspect for each mentioned entity; it is implemented in Python and available as a script and via an online demo. It is accomp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b87d3f9226ac92d8f6930bdf35626a09
https://doi.org/10.1109/jcdl.2019.00104
https://doi.org/10.1109/jcdl.2019.00104
Publikováno v:
EMNLP
The Conference on Empirical Methods in Natural Language Processing
MADOC-University of Mannheim
The Conference on Empirical Methods in Natural Language Processing
MADOC-University of Mannheim
The goal of Open Information Extraction (OIE) is to extract surface relations and their arguments from natural-language text in an unsupervised, domain-independent manner. In this paper, we propose MinIE, an OIE system that aims to provide useful, co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::26af63b31da1931fbb05673559010ed4
https://doi.org/10.18653/v1/d17-1278
https://doi.org/10.18653/v1/d17-1278