CLEF-HIPE

This repository contains code and models to solve the HIPE (Identifying Historical People, Places and other Entities) evaluation compaign from the Impresso Project.

It also includes code and models from the following papers:

• Triple E - Effective Ensembling of Embeddings and Language Models for NER of Historical German
• hmBERT: Historical Multilingual Language Models for Named Entity Recognition

We are heavily working on better models for historic texts, so please star or watch this repository!

Triple E - Effective Ensembling of Embeddings and Language Models for NER of Historical German

In this section we give a brief overview of how to reproduce the results from our paper.

As we heavily use Flair and Transformers for our experiments, you should find the relevant scripts in the experiments/clef-hipe-2020 folder:

• word-embeddings: includes scripts for the experiments with different word embeddings
• flair-embeddings: includes scripts for the experiments with different Flair embeddings
• stacked: combines word, Flair and Transformer-based embeddings

hmBERT: Historical Multilingual Language Models for Named Entity Recognition

For CLEF-HIPE 2022 we have released multilingual language models: hmBERT. A detailed description of our final system can be found here. Additional information about our released language models for the historic domain is also available here.

All experiments, released language models and fine-tuned NER models are described in our new "hmBERT: Historical Multilingual Language Models for Named Entity Recognition" paper.

Changelog

• 09.09.2022: Presentation slides of our HIPE-2022 submission can be found here.
• 03.06.2022: Preprint of our HIPE-2022 system overview paper is available: "hmBERT: Historical Multilingual Language Models for Named Entity Recognition"
• 22.03.2022: Initial version for our HIPE-2022 submission here.
• 06.12.2021: Release of smaller multilingual Historic Language Models (ranging from 2-8 layers) - more information here.
• 18.11.2021: Release of first multilingual and monolingual Historic Language Models - more information here.
• 04.11.2021: We will take part in the upcoming CLEF-HIPE 2022 Shared Task. We plan to release new language models before the start of the official shared task very soon.
• 30.10.2021: Manually sentence-segmented Development and Test data for English was added.
• 30.11.2020: Initial version of this repository.

Citation

You can use the following BibTeX entry for our HIPE-2020 submission:

@inproceedings{DBLP:conf/clef/SchweterM20,
  author    = {Stefan Schweter and
               Luisa M{\"{a}}rz},
  editor    = {Linda Cappellato and
               Carsten Eickhoff and
               Nicola Ferro and
               Aur{\'{e}}lie N{\'{e}}v{\'{e}}ol},
  title     = {Triple {E} - Effective Ensembling of Embeddings and Language Models
               for {NER} of Historical German},
  booktitle = {Working Notes of {CLEF} 2020 - Conference and Labs of the Evaluation
               Forum, Thessaloniki, Greece, September 22-25, 2020},
  series    = {{CEUR} Workshop Proceedings},
  volume    = {2696},
  publisher = {CEUR-WS.org},
  year      = {2020},
  url       = {http://ceur-ws.org/Vol-2696/paper\_173.pdf},
  timestamp = {Tue, 27 Oct 2020 17:12:48 +0100},
  biburl    = {https://dblp.org/rec/conf/clef/SchweterM20.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

And the following BiBTeX entry for our latest HIPE-2022 submission:

@inproceedings{DBLP:conf/clef/SchweterMSC22,
  author    = {Stefan Schweter and
               Luisa M{\"{a}}rz and
               Katharina Schmid and
               Erion {\c{C}}ano},
  editor    = {Guglielmo Faggioli and
               Nicola Ferro and
               Allan Hanbury and
               Martin Potthast},
  title     = {hmBERT: Historical Multilingual Language Models for Named Entity Recognition},
  booktitle = {Proceedings of the Working Notes of {CLEF} 2022 - Conference and Labs
               of the Evaluation Forum, Bologna, Italy, September 5th - to - 8th,
               2022},
  series    = {{CEUR} Workshop Proceedings},
  volume    = {3180},
  pages     = {1109--1129},
  publisher = {CEUR-WS.org},
  year      = {2022},
  url       = {http://ceur-ws.org/Vol-3180/paper-87.pdf},
  timestamp = {Wed, 10 Aug 2022 16:26:45 +0200},
  biburl    = {https://dblp.org/rec/conf/clef/SchweterMSC22.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

Acknowledgements

Research supported with Cloud TPUs from Google's TPU Research Cloud (TRC). Many Thanks for providing access to the TPUs ❤️