Semanlink - Favoris ; Artificial Intelligence AND Named Entity Recognition

a language
model with access to information available in a
KB, no assumptions
about the availability of additional components
(such as Named Entity Taggers) or annotations

> While classes of
named entities (e.g., person or location) occur frequently,
each individual name (e.g, Atherton or
Zhouzhuang) may be observed infrequently even
in a very large corpus of text. As a result language
models learn to represent accurately only the most
popular named entities

> knowing that Alice is a name
used to refer to a person should give ample information
about the context in which the word may
occur (e.g., Bob visited Alice).

> ---

> extends a traditional **RNN LM**

> we enhance a traditional LM with a
gating mechanism that controls whether a particular
word is modeled as a general word or as a reference
to an entity
>
> We train the model end-to-end
with only the traditional predictive language modeling
perplexity objective
>
> KALM is trained end-to-end using
a predictive objective on large corpus of text.

> To the best of our knowledge, KALM is the first
unsupervised neural NER approach.

> KALM extends a traditional, RNN-based neural
LM.

2022-08-31 A propos

[1807.00745] Training a Neural Network in a Low-Resource Setting on Automatically Annotated Noisy Data

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2022-07-18 A propos

DataBorg - Knowledge management simplified

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2022-05-14 A propos

[1910.06294] Training Compact Models for Low Resource Entity Tagging using Pre-trained Language Models

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2022-03-31 A propos

Studio Ousia sur Twitter : "Now using LUKE is easier than ever!" / Twitter

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2022-03-15 A propos

MasakhaNER: Named Entity Recognition for African Languages | MIT Press

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2021-10-14 A propos

(((ل()(ل() 'yoav))))👾 sur Twitter : "my two cents on why NLP as a field is focusing on the ML-ish / algorithmic / leaderboard-ish aspects (incl., now, LLMs) and not on the underlying language phenomena: it is just so much easier, on so many levels."

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2021-08-30 A propos

[2103.11811] MasakhaNER: Named Entity Recognition for African Languages

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2021-07-06 A propos

Christopher Dengsø sur Twitter : "The moderation API now detects addresses in addition to other personal details."

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2021-03-09 A propos

asahi417/tner: Language model finetuning on NER

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2021-03-04 A propos

Named Entity Recognition without Labelled Data: A Weak Supervision Approach (2020)

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2021-02-24 A propos

Named Entity Recognition without Labelled Data: A Weak Supervision Approach (2020) (slides)

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2021-02-24 A propos

Why we switched from Spacy to Flair to anonymize French case law | by Michaël Benesty | Towards Data Science

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2021-02-10 A propos

kamalkraj/BERT-NER: Pytorch-Named-Entity-Recognition-with-BERT

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2021-02-07 A propos

Custom NLP Approaches to Data Anonymization | by Omri Mendels | Towards Data Science

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2021-02-01 A propos

[2011.06993] FLERT: Document-Level Features for Named Entity Recognition

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2020-12-01 A propos

[2001.08053] Contextualized Embeddings in Named-Entity Recognition: An Empirical Study on Generalization

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2020-10-01 A propos

Unsupervised NER using BERT - Hands-on NLP model review - Quora

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2020-03-06 A propos

[2002.11402] Detecting Potential Topics In News Using BERT, CRF and Wikipedia

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2020-02-27 A propos

pfliu-nlp/Named-Entity-Recognition-NER-Papers: An elaborate and exhaustive paper list for Named Entity Recognition (NER)

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2020-01-12 A propos

Interpretable Named entity recognition with keras and LIME – Depends on the definition

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2020-01-09 A propos

Named Entity Recognition with Bert – Depends on the definition

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2020-01-09 A propos

How to build deep neural network for custom NER with Keras

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2020-01-07 A propos

Custom Named Entity Recognition Using spaCy - Towards Data Science

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2019-12-31 A propos

NER algo benchmark: spaCy, Flair, m-BERT and camemBERT on anonymizing French commercial legal cases

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2019-12-17 A propos

Named Entity Recognition with Pytorch Transformers – Pierre-Yves Vandenbussche

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2019-12-11 A propos - Copie locale

Meetup Paris #40 : Beyond plain text: elasticsearch’s annotated text field type (en anglais) - YouTube

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2019-11-24 A propos

[1908.08983] A Little Annotation does a Lot of Good: A Study in Bootstrapping Low-resource Named Entity Recognizers

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2019-08-28 A propos

[1812.09449] A Survey on Deep Learning for Named Entity Recognition

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2019-04-24 A propos

Phoneme Recognition (caveat emptor) – CMUSphinx Open Source Speech Recognition

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2019-04-16 A propos

[1806.04411] Named Entity Recognition with Extremely Limited Data

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2019-04-11 A propos

Evaluating Solutions for Named Entity Recognition | Novetta.com (2018)

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2019-04-11 A propos

A machine learning model to understand fancy abbreviations, trained on Tolkien

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2019-04-03 A propos

A SIMPLE ALGORITHM FOR IDENTIFYING ABBREVIATION DEFINITIONS IN BIOMEDICAL TEXT

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2019-04-03 A propos

nlp - Abbreviation detection - Stack Overflow

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Acronyms (NLP)

2019-04-03 A propos

How Search Engines Might Expand Abbreviations in Queries - SEO by the Sea ⚓

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Acronyms (NLP)

2019-04-03 A propos

Acronym Recognition - Recognizing acronyms in Swedish texts

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Acronyms (NLP)

2019-04-03 A propos

[1601.01343] Joint Learning of the Embedding of Words and Entities for Named Entity Disambiguation

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2019-01-27 A propos

Effect of Non-linear Deep Architecture in Sequence Labeling

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2018-10-22 A propos

Deep Learning for Named Entity Recognition #1: Public Datasets and Annotation Methods

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Named Entity Recognition

2018-10-15 A propos

Named Entity Recognition and Classification with Scikit-Learn

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2018-09-16 A propos

A Named Entity Recognition Shootout for German (2018)

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Named Entity Recognition

2018-07-12 A propos

[1806.04470] Design Challenges and Misconceptions in Neural Sequence Labeling

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2018-06-28 A propos

[1404.5367] Lexicon Infused Phrase Embeddings for Named Entity Resolution

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2018-05-22 A propos

BiLSTM-CNN-CRF Implementation for Sequence Tagging

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2018-05-21 A propos

Named Entity Recognition and the Road to Deep Learning (2017)

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> the old
and the new-style NLP are not diametrically
opposed: just as it is possible (and useful!) to
incorporate neural-network features into a CRF,
CRFs have influenced some of the best deep
learning models for sequence labelling

This blog post go through the ways of doing NER, starting with CRF:

- When you develop a CRF,
a lot of time goes into finding feature functions (Does a word start with a capital? Is it uppercase? Is it a digit?...) 
- Pb: semantic similarity between words. 
- Gazetteers: lists with names of people, locations and organizations that are known in advance.
- feed Word Embeddings to a CRF: one way is to cluster a set
of word embeddings by distributional similarity, and
provide the CRF with the cluster IDs of a token and its
context words.
- Use word and character based embeddings
- LSTM not good enough -> biLSTM
- **biLSTM predict all labels independently of each other -> add a CRF layer** which outputs a matrix of transition scores between two states: dynamic programming can help find the optimal tag sequence for the sentence

2018-05-20 A propos

Named Entity Recognition and the Stanford NER Software (slides)

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2018-05-20 A propos

Named Entity Recognition: Milestone Papers, Models and Technologies (2017)

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2018-05-20 A propos

Stanford Named Entity Recognizer

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Stanford NER

2018-05-20 A propos

How to Train your Own Model with NLTK and Stanford NER Tagger? (for English, French, German…)

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2018-05-20 A propos

Exploring neural architectures for NER (CS224N 2018)

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2018-04-05 A propos

SPACY'S ENTITY RECOGNITION MODEL: incremental parsing with Bloom embeddings & residual CNNs - YouTube

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2018-03-06 A propos

Effective Word Representation for Named Entity Recognition (2017)

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2018-03-06 A propos

Deep learning with word embeddings improves biomedical named entity recognition | Bioinformatics | Oxford Academic (2017)

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2018-03-05 A propos

[1508.01991] Bidirectional LSTM-CRF Models for Sequence Tagging

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2018-03-05 A propos

Sequence Tagging with Tensorflow

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2018-03-05 A propos

[1603.01360] Neural Architectures for Named Entity Recognition

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2018-03-05 A propos

A survey of named entity recognition and classification (2006)

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Named Entity Recognition

2018-03-05 A propos

Named Entity Recognition using Word Embedding as a Feature (2016)

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2017-10-01 A propos

Dexter, an Open Source Framework for Entity Linking

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2014-10-20 A propos

Extraction de la semantique

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2014-06-18 A propos

Bing - Knowledge Widget (Beta)

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2014-04-04 A propos

Context-based Entity Linking | Blog | graus.nu

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Named Entity Recognition

2013-07-18 A propos

NERD: Named Entity Recognition and Disambiguation

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2013-07-10 A propos

Wikilinks - Information Extraction and Synthesis Laboratory

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Wikilinks Corpus

2013-03-12 A propos

Learning from Big Data: 40 Million Entities in Context

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Wikilinks Corpus

2013-03-12 A propos

Duped by Dupes | Wavii Blog

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2012-08-25 A propos

LINDEN: Linking Named Entities with Knowledge Base via Semantic Knowledge

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2012-04-19 A propos

A Spectrometry of Linked Data

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Entity mining is still a troublesome open problem. In past years many approaches allowed to automate the generation of equivalence links between references using schema matching or various heuristics based on the recognition of similar property values. In contrast, few of them considered the analysis of the network of equivalence links (“equivalence network”) as an indication of the likelihood and strength of the equivalence.

Could a URI reference (URIRef) be thought as exactly “attached” to its referent? Could it make sense to talk about entity “identifiers” or would it be better to talk about more ambiguous “references”, i.e., placeholders for any model that satisfies the formal semantics of the Semantic Web (Hayes)? Booth observes that the aforementioned question, which in the past has been often regarded as fundamental in the debate about identity on the Web, is relatively unimportant. As long as an entity, identified by whatsoever URIRef, is associated to at least one description containing machine understandable information, this information can be automatically processed and used by applications.

2012-04-16 A propos