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NLP event AND Knowledge Graphs

Common descendants

KD-MKB paper

21 Documents

Specializing Static and Contextual Embeddings in the Medical Domain Using Knowledge Graphs: Let’s Keep It Simple - ACL Anthology (2022)

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2023-10-11 About

[2008.12813] HittER: Hierarchical Transformers for Knowledge Graph Embeddings

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2022-06-30 About

Knowledge Graphs in Natural Language Processing @ ACL 2021 | by Michael Galkin | Aug, 2021

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2021-08-06 About

[2009.12030] AutoETER: Automated Entity Type Representation for Knowledge Graph Embedding

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2021-05-17 About

Knowledge Base Embedding By Cooperative Knowledge Distillation - ACL Anthology

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KD-MKB paper

2020-12-05 About

[2010.01057] LUKE: Deep Contextualized Entity Representations with Entity-aware Self-attention

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2020-11-26 About

Knowledge Graphs in NLP @ EMNLP 2020 | by Michael Galkin | Nov, 2020 | Medium

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2020-11-24 About

Knowledge Graphs in Natural Language Processing @ ACL 2020 | by Michael Galkin

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2020-07-12 About

Learning to Tag OOV Tokens by Integrating Contextual Representation and Background Knowledge (ACL Anthology 2020)

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Aim to leverage both contextual representation of input text (deep LMs)  and  knowledge derived
from curated KBs ([Wordnet](tag:wordnet)) to improve [slot tagging](tag:slot_tagging) in the presence of [out-of-vocab](tag:oov) words ([few-shot scenario](tag:few_shot_learning))

Method:

1. retrieve potentially relevant KB entities and
encode them into distributed representations that
describe global graph-structured information
2. BERT encoder
layer to capture context-aware representations of
the sequence and attend to the KB embeddings
using multi-level graph attention
3. integrate
BERT embeddings and the KB embeddings
to predict the slot type

Contributions:

1. feasibility of applying lexical ontology
to facilitate recognizing OOV words. First to consider the large-scale background
knowledge for enhancing context-aware
slot tagging models.
2. a knowledge integration mechanism that uses multi-level graph
attention to model explicit lexical relations.
3.experiments on two benchmark datasets

> our method makes a notable difference in a
scenario where samples are linguistically diverse,
and large vocab exists.

(Better improvements when using RNN than BERT, because BERT already contains a lot of background knowledge)

2020-07-04 About

[1909.04164] Knowledge Enhanced Contextual Word Representations

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2020-05-13 About

[1906.01195] Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs

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2020-04-30 About

Advancing Natural Language Processing (NLP) for Enterprise Domains

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2020-01-07 About

Barack’s Wife Hillary: Using Knowledge Graphs for Fact-Aware Language Modeling (ACL 2019)

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2019-11-17 About

[1905.07129] ERNIE: Enhanced Language Representation with Informative Entities

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2019-08-05 About

Knowledge graphs in Natural Language Processing @ ACL 2019 - Michael Galkin

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2019-08-05 About

A2N: Attending to Neighbors for Knowledge Graph Inference - ACL 2019

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2019-07-31 About

thunlp/OpenKE: An Open-Source Package for Knowledge Embedding (KE)

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2019-04-23 About

Multi-Task Identification of Entities, Relations, and Coreference for Scientific Knowledge Graph Construction - ACL Anthology

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2019-02-09 About

Romain Vial (Hyperlex) at Paris NLP meetup, slides

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2019-01-24 About

Multi-Task Identification of Entities, Relations, and Coreference for Scientific Knowledge Graph Construction

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2018-11-04 About

[1809.00782] Open Domain Question Answering Using Early Fusion of Knowledge Bases and Text

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2018-09-06 About