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Found 15 papers, 6 papers with code
If You Build Your Own NER Scorer, Non-replicable Results Will Come
We propose best practices to increase the replicability of NER evaluations by increasing transparency regarding the handling of improper label sequences.
Effective Architectures for Low Resource Multilingual Named Entity Transliteration
In this paper, we evaluate LSTM, biLSTM, GRU, and Transformer architectures for the task of name transliteration in a many-to-one multilingual paradigm, transliterating from 590 languages to English.
Detecting Unassimilated Borrowings in Spanish: An Annotated Corpus and Approaches to Modeling
This work presents a new resource for borrowing identification and analyzes the performance and errors of several models on this task.
ParaNames: A Massively Multilingual Entity Name Corpus
This preprint describes work in progress on ParaNames, a multilingual parallel name resource consisting of names for approximately 14 million entities.
Toward More Meaningful Resources for Lower-resourced Languages
We then discuss the importance of creating annotation for lower-resourced languages in a thoughtful and ethical way that includes the languages' speakers as part of the development process.
Multilingual Open Text 1.0: Public Domain News in 44 Languages
We present a new multilingual corpus containing text in 44 languages, many of which have relatively few existing resources for natural language processing.
Overview of ADoBo 2021: Automatic Detection of Unassimilated Borrowings in the Spanish Press
This paper summarizes the main findings of the ADoBo 2021 shared task, proposed in the context of IberLef 2021.
SeqScore: Addressing Barriers to Reproducible Named Entity Recognition Evaluation
To address a looming crisis of unreproducible evaluation for named entity recognition, we propose guidelines and introduce SeqScore, a software package to improve reproducibility.
Macro-Average: Rare Types Are Important Too
While traditional corpus-level evaluation metrics for machine translation (MT) correlate well with fluency, they struggle to reflect adequacy.
Mining Wikidata for Name Resources for African Languages
This work supports further development of language technology for the languages of Africa by providing a Wikidata-derived resource of name lists corresponding to common entity types (person, location, and organization).
TMR: Evaluating NER Recall on Tough Mentions
We propose the Tough Mentions Recall (TMR) metrics to supplement traditional named entity recognition (NER) evaluation by examining recall on specific subsets of "tough" mentions: unseen mentions, those whose tokens or token/type combination were not observed in training, and type-confusable mentions, token sequences with multiple entity types in the test data.
MasakhaNER: Named Entity Recognition for African Languages
We take a step towards addressing the under-representation of the African continent in NLP research by creating the first large publicly available high-quality dataset for named entity recognition (NER) in ten African languages, bringing together a variety of stakeholders.
The Effectiveness of Morphology-aware Segmentation in Low-Resource Neural Machine Translation
This paper evaluates the performance of several modern subword segmentation methods in a low-resource neural machine translation setting.
The Challenges of Optimizing Machine Translation for Low Resource Cross-Language Information Retrieval
When performing cross-language information retrieval (CLIR) for lower-resourced languages, a common approach is to retrieve over the output of machine translation (MT).
SARAL: A Low-Resource Cross-Lingual Domain-Focused Information Retrieval System for Effective Rapid Document Triage
In this paper we present an end-to-end cross-lingual information retrieval (CLIR) and summarization system for low-resource languages that 1) enables English speakers to search foreign language repositories of text and audio using English queries, 2) summarizes the retrieved documents in English with respect to a particular information need, and 3) provides complete transcriptions and translations as needed.
