• Corpus ID: 3542854

TAMU at KBP 2017: Event Nugget Detection and Coreference Resolution

@article{Choubey2017TAMUAK,
  title={TAMU at KBP 2017: Event Nugget Detection and Coreference Resolution},
  author={Prafulla Kumar Choubey and Ruihong Huang},
  journal={ArXiv},
  year={2017},
  volume={abs/1711.02162}
}
In this paper, we describe TAMU's system submitted to the TAC KBP 2017 event nugget detection and coreference resolution task. Our system builds on the statistical and empirical observations made on training and development data. We found that modifiers of event nuggets tend to have unique syntactic distribution. Their parts-of-speech tags and dependency relations provides them essential characteristics that are useful in identifying their span and also defining their types and realis status… 

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References

SHOWING 1-10 OF 30 REFERENCES

CMU-LTI at KBP 2016 Event Nugget Track

TLDR
The CMU LTI team’s participation in TAC KBP 2016 event nugget track is described, and their feature based English Nugget Detection and Coreference systems both rank number 2 among all the participants.

CMUML Micro-Reader System for KBP 2016 Cold Start Slot Filling, Event Nugget Detection, and Event Argument Linking

TLDR
An overview of the CMUML’s Micro-Reader system for three TAC KBP tasks: Cold Start Slot Filling (SF), Event Nugget Detection and Coreference (EN); and Event Argument Extraction and Linking (EAL).

AIPHES-HD system at TAC KBP 2016: Neural Event Trigger Span Detection and Event Type and Realis Disambiguation with Word Embeddings

TLDR
A simple but effective system which uses a Bi-Directional LSTM with embeddings short-cuts to the output for Event Trigger detection and simple Logistic Regression Classifiers with event trigger context features based on word embeddINGS for Event Type and Realis detection is implemented.

Event Nugget Detection Task : UMBC systems

TLDR
This paper describes the Event Nugget Detection system that was submitted to the TAC KBP 2016 Event Track and its performance was low; the F1 measure was low.

Illinois CCG Entity Discovery and Linking, Event Nugget Detection and Co-reference, and Slot Filler Validation Systems for TAC 2016

The University of Illinois CCG team participated in three TAC 2016 tasks: Entity Discovery and Linking (EDL); Event Nugget Detection and Co-reference (ENDC); and Slot Filler Validation (SFV). The EDL

Overview of SYDNEY System for TAC KBP 2015 Event Nugget Detection

TLDR
Developing experiments indicate that Brown cluster, Nomlex and WordNet features are complementary with more improvement from Word net features, and the contribution of features aimed at improving generalisation is explored.

Stanford’s Multi-Pass Sieve Coreference Resolution System at the CoNLL-2011 Shared Task

TLDR
The coreference resolution system submitted by Stanford at the CoNLL-2011 shared task was ranked first in both tracks, with a score of 57.8 in the closed track and 58.3 in the open track.

SoochowNLP Team System Description for 2016 KBP Slot Filling and Nugget Detection Tasks

TLDR
The baseline is a pattern based search engine, which generate a query by using entity name and retrieves pseudo-relevant documents and determines them as reliable candidate fillers when meeting a predefined relation pattern.

Improving DISCERN with Deep Learning

TLDR
IHMC designed and implemented two variants of an event-detection system that used manually created rules and another one that used rules learned using multiple deep neural networks, both of which were applied to two tasks in the NIST TAC KBP 2016 Event Track.

University of Washington TAC-KBP 2016 System Description

TLDR
The University of Washington’s event extraction system was composed of three components: Evento, a CRFbased extractor, NomEvent, which makes use a lexicon to build features to identify nominal triggers, and NewsSpike, which uses an unsupervised training process to produce a highprecision extractor.