Deucalion and Pie lemmatizers - Revision history

AurelienBerra: Add link for Deucalion as on online service

2023-05-28T15:23:40Z

Add link for Deucalion as on online service

← Older revision		Revision as of 16:23, 28 May 2023
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	* Latin Model: https://github.com/PonteIneptique/latin-lasla-models		* Latin Model: https://github.com/PonteIneptique/latin-lasla-models
	* Pie-Extended: https://github.com/hipster-philology/nlp-pie-taggers		* Pie-Extended: https://github.com/hipster-philology/nlp-pie-taggers
			* Deucalion, a Web interface for Flask-Pie: https://dh.chartes.psl.eu/deucalion/ (Ancient Greek, and Latin, as well as Old French, Modern French, Early Modern French, and Middle Dutch)

	== Author ==		== Author ==

JoelKalvesmaki at 14:49, 25 May 2023

2023-05-25T14:49:26Z

← Older revision		Revision as of 15:49, 25 May 2023
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	[[category:lemmatisation]]		[[category:lemmatisation]]
	[[category:tools]]		[[category:tools]]
	~~[[category:programming]]~~
	[[category:linguistics]]		[[category:linguistics]]

JoelKalvesmaki: Added category

2023-05-25T14:48:50Z

Added category

← Older revision		Revision as of 15:48, 25 May 2023
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	[[category:tools]]		[[category:tools]]
	[[category:programming]]		[[category:programming]]
			[[category:linguistics]]

ThibaultClerice at 11:40, 22 September 2020

2020-09-22T11:40:13Z

← Older revision		Revision as of 12:40, 22 September 2020
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	* Pie: https://github.com/emanjavacas/pie		* Pie: https://github.com/emanjavacas/pie
	* ~~Deucalion (with LASLA data)~~: https://github.com/~~chartes~~/~~deucalion~~-~~model~~-~~lasla~~		* Latin Model: https://github.com/PonteIneptique/latin-lasla-models
			* Pie-Extended: https://github.com/hipster-philology/nlp-pie-taggers

	== Author ==		== Author ==
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	'''Pie''' is a language independant lemmatizer implemented in python and built for "variation-rich languages" which includes Latin. It's a deep learning tool that can be trained and retrained with data in TSV format. As of 2019, it seems to be one of the state-of-the-art lemmatizers in terms of results. It can be trained jointly on morphology, POS and lemmatization tasks.		'''Pie''' is a language independant lemmatizer implemented in python and built for "variation-rich languages" which includes Latin. It's a deep learning tool that can be trained and retrained with data in TSV format. As of 2019, it seems to be one of the state-of-the-art lemmatizers in terms of results. It can be trained jointly on morphology, POS and lemmatization tasks.

	=== ~~Deucalion~~ ===		=== Pie Extended ===

	~~Deucalion is~~ :		Pie-Extended an extension built on top of Pie to ease its use as a tagger: it handles downloading of models, tokenization and post-/pre-processing. It requires python > 3.6 and just enough knowledge about installing libraries in Python as well as using a Command Line Interface.

	* a model for the lemmatizer Pie ~~([https://github.com/chartes/deucalion-model-lasla/blob/master/lemma.split-morph.tar .tar file on github]~~)		=== Deucalion (now Flask Pie) ===
	* a web-application that can be easily deployed for running a lemmatization service. It runs on Python3 and flask
	* a [https://hub.docker.com/r/ponteineptique/deucalion-model-lasla Docker Image ] that makes running it even simpler

	In terms of statistics, the corpus was trained over around 1.3 million tokens (June 2019). The accuracy are described in the [https://github.com/chartes/deucalion-model-lasla/tree/master/information information] folder of the image but we can note the following accuracies:		Flask-Pie (previously known as Deucalion) provides adapters to server Pie models over HTTP servers.

	* Lemmatization : 97,52 %
	* Part-Of-~~Speech: 96.55 %~~
	* Morphology
	** Voice : 99.18 %
	** Mood : 98.36 %
	** Degree : 98.30 %
	** Number : 97.88 %
	** Person : 99.18 %
	** Tense : 98.75 %
	** Tense : 93.74 %
	** Gender : 97.27 % (~~Note that not all words were annotated in genders in the LASLA data, specifically not the nouns~~)

	~~A version is hosted at [https://dev~~.~~chartes.psl.eu/deucalion/models/lasla/ the École des Chartes]~~

	== Bibliography ==		== Bibliography ==

GabrielBodard: cat

2019-08-30T14:02:23Z

cat

← Older revision		Revision as of 15:02, 30 August 2019
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	* Thibault Clérice. (2019, February 1). chartes/deucalion-model-lasla: LASLA Latin Lemmatizer - Alpha (Version 0.0.1). Zenodo. http://doi.org/10.5281/zenodo.2554847		* Thibault Clérice. (2019, February 1). chartes/deucalion-model-lasla: LASLA Latin Lemmatizer - Alpha (Version 0.0.1). Zenodo. http://doi.org/10.5281/zenodo.2554847

	[[category:lemmatisation]] [[category:tools]]		[[category:lemmatisation]]
			[[category:tools]]
			[[category:programming]]

GabrielBodard: exposed URLs in available

2019-06-04T16:42:27Z

exposed URLs in available

← Older revision		Revision as of 17:42, 4 June 2019
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	== Available ==		== Available ==

	* [https://github.com/emanjavacas/pie ~~Pie]~~		* Pie: https://github.com/emanjavacas/pie
	* [https://github.com/chartes/deucalion-model-lasla ~~Deucalion (with LASLA data)]~~		* Deucalion (with LASLA data): https://github.com/chartes/deucalion-model-lasla

	== Author ==		== Author ==
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	'''Pie''' is a language independant lemmatizer implemented in python and built for "variation-rich languages" which includes Latin. It's a deep learning tool that can be trained and retrained with data in TSV format. As of 2019, it seems to be one of the state-of-the-art lemmatizers in terms of results. It can be trained jointly on morphology, POS and lemmatization tasks.		'''Pie''' is a language independant lemmatizer implemented in python and built for "variation-rich languages" which includes Latin. It's a deep learning tool that can be trained and retrained with data in TSV format. As of 2019, it seems to be one of the state-of-the-art lemmatizers in terms of results. It can be trained jointly on morphology, POS and lemmatization tasks.


	=== Deucalion ===		=== Deucalion ===
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	== Bibliography ==		== Bibliography ==


	* D. Longrée, C. Philippart de Foy & G. Purnelle. « Structures phrastiques et analyse automatique des données morphosyntaxiques : le projet LatSynt », in S. Bolasco, I. Chiari & L. Giuliano (eds), Statistical Analysis of Textual Data, Proceedings of 10th International Conference Journées d'Analyse statistique des Données Textuelles, 9-11 June 2010, Sapienza University of Rome, Rome, LED, pp. 433-442.		* D. Longrée, C. Philippart de Foy & G. Purnelle. « Structures phrastiques et analyse automatique des données morphosyntaxiques : le projet LatSynt », in S. Bolasco, I. Chiari & L. Giuliano (eds), Statistical Analysis of Textual Data, Proceedings of 10th International Conference Journées d'Analyse statistique des Données Textuelles, 9-11 June 2010, Sapienza University of Rome, Rome, LED, pp. 433-442.

ThibaultClerice: Reorganization proposal

2019-06-04T16:39:02Z

Reorganization proposal

← Older revision		Revision as of 17:39, 4 June 2019
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	== ~~Pie~~ ==		== Available ==

	[https://github.com/emanjavacas/pie Pie] ~~is a language independant lemmatizer implemented in python and built for "variation~~-~~rich languages" which includes Latin. It's a deep learning tool that can be trained and retrained~~ with data ~~in TSV format. As of 2019, it seems to be one of the state-of-the-art lemmatizers in terms of results. It can be trained jointly on morphology, POS and lemmatization tasks.~~		* [https://github.com/emanjavacas/pie Pie]
			* [https://github.com/chartes/deucalion-model-lasla Deucalion (with LASLA data)]

	== ~~Deucalion~~ ==		== Author ==

	~~[https://github~~.~~com/chartes/deucalion~~-~~model~~-~~lasla~~ Deucalion ~~(with LASLA data)]~~ is :		* Enrique Manjavas
			* Mike Kestemont
			* Thibault Clérice

			== Description ==

			'''Pie''' is a language independant lemmatizer implemented in python and built for "variation-rich languages" which includes Latin. It's a deep learning tool that can be trained and retrained with data in TSV format. As of 2019, it seems to be one of the state-of-the-art lemmatizers in terms of results. It can be trained jointly on morphology, POS and lemmatization tasks.


			=== Deucalion ===

			Deucalion is :

	* a model for the lemmatizer Pie ([https://github.com/chartes/deucalion-model-lasla/blob/master/lemma.split-morph.tar .tar file on github])		* a model for the lemmatizer Pie ([https://github.com/chartes/deucalion-model-lasla/blob/master/lemma.split-morph.tar .tar file on github])
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	A version is hosted at [https://dev.chartes.psl.eu/deucalion/models/lasla/ the École des Chartes]		A version is hosted at [https://dev.chartes.psl.eu/deucalion/models/lasla/ the École des Chartes]

	== Bibliography ==		== Bibliography ==

GabrielBodard: cat

2019-06-04T16:32:27Z

cat

← Older revision		Revision as of 17:32, 4 June 2019
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	* Thibault Clérice. (2019, February 1). chartes/deucalion-model-lasla: LASLA Latin Lemmatizer - Alpha (Version 0.0.1). Zenodo. http://doi.org/10.5281/zenodo.2554847		* Thibault Clérice. (2019, February 1). chartes/deucalion-model-lasla: LASLA Latin Lemmatizer - Alpha (Version 0.0.1). Zenodo. http://doi.org/10.5281/zenodo.2554847

	[[category:~~lemmatization~~]] [[category:tools]]		[[category:lemmatisation]] [[category:tools]]

ThibaultClerice: Added categories

2019-06-04T16:31:16Z

Added categories

← Older revision		Revision as of 17:31, 4 June 2019
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	* Enrique Manjavacas & Mike Kestemont. (2019, January 17). emanjavacas/pie v0.1.3 (Version v0.1.3). Zenodo. http://doi.org/10.5281/zenodo.2542537		* Enrique Manjavacas & Mike Kestemont. (2019, January 17). emanjavacas/pie v0.1.3 (Version v0.1.3). Zenodo. http://doi.org/10.5281/zenodo.2542537
	* Thibault Clérice. (2019, February 1). chartes/deucalion-model-lasla: LASLA Latin Lemmatizer - Alpha (Version 0.0.1). Zenodo. http://doi.org/10.5281/zenodo.2554847		* Thibault Clérice. (2019, February 1). chartes/deucalion-model-lasla: LASLA Latin Lemmatizer - Alpha (Version 0.0.1). Zenodo. http://doi.org/10.5281/zenodo.2554847

			[[category:lemmatization]] [[category:tools]]

ThibaultClerice: Deucalion and Pie page creation

2019-06-04T16:27:31Z

Deucalion and Pie page creation

New page

== Pie ==

[https://github.com/emanjavacas/pie Pie] is a language independant lemmatizer implemented in python and built for "variation-rich languages" which includes Latin. It's a deep learning tool that can be trained and retrained with data in TSV format. As of 2019, it seems to be one of the state-of-the-art lemmatizers in terms of results. It can be trained jointly on morphology, POS and lemmatization tasks.

== Deucalion ==

[https://github.com/chartes/deucalion-model-lasla Deucalion (with LASLA data)] is :

* a model for the lemmatizer Pie ([https://github.com/chartes/deucalion-model-lasla/blob/master/lemma.split-morph.tar .tar file on github])
* a web-application that can be easily deployed for running a lemmatization service. It runs on Python3 and flask
* a [https://hub.docker.com/r/ponteineptique/deucalion-model-lasla Docker Image ] that makes running it even simpler

In terms of statistics, the corpus was trained over around 1.3 million tokens (June 2019). The accuracy are described in the [https://github.com/chartes/deucalion-model-lasla/tree/master/information information] folder of the image but we can note the following accuracies:

* Lemmatization : 97,52 %
* Part-Of-Speech: 96.55 %
* Morphology
** Voice : 99.18 %
** Mood : 98.36 %
** Degree : 98.30 %
** Number : 97.88 %
** Person : 99.18 %
** Tense : 98.75 %
** Tense : 93.74 %
** Gender : 97.27 % (Note that not all words were annotated in genders in the LASLA data, specifically not the nouns)

A version is hosted at [https://dev.chartes.psl.eu/deucalion/models/lasla/ the École des Chartes]
== Bibliography ==

* D. Longrée, C. Philippart de Foy & G. Purnelle. « Structures phrastiques et analyse automatique des données morphosyntaxiques : le projet LatSynt », in S. Bolasco, I. Chiari & L. Giuliano (eds), Statistical Analysis of Textual Data, Proceedings of 10th International Conference Journées d'Analyse statistique des Données Textuelles, 9-11 June 2010, Sapienza University of Rome, Rome, LED, pp. 433-442.
* D. Longrée & C. Poudat, « New Ways of Lemmatizing and Tagging Classical and post-Classical Latin: the LATLEM project of the LASLA », in P. Anreiter & M. Kienpointner (éd.), Proceedings of the 15th International Colloquium on Latin Linguistics, (Innsbrucker Beiträge zur Sprachwissenschaft), Innsbruck, 2010, pp. 683-694.
* D. Longrée & C. Philippart de Foy & G. Purnelle, « Subordinate clause boundaries and word order in Latin: the contribution of the L.A.S.L.A. syntactic parser project LatSynt », in P. Anreiter & M. Kienpointner, éd.), Proceedings of the 15th International Colloquium on Latin Linguistics, (Innsbrucker Beiträge zur Sprachwissenschaft), Innsbruck, 2010, pp. 673-681.
* D. Longrée & Poudat C., « Variations langagières et annotation morphosyntaxique du latin classique », TAL, 50 – n° 2/2009, Special issue on "Natural Language Processing and Ancient Languages", pp. 129-148.
* Enrique Manjavacas & Mike Kestemont. (2019, January 17). emanjavacas/pie v0.1.3 (Version v0.1.3). Zenodo. http://doi.org/10.5281/zenodo.2542537
* Thibault Clérice. (2019, February 1). chartes/deucalion-model-lasla: LASLA Latin Lemmatizer - Alpha (Version 0.0.1). Zenodo. http://doi.org/10.5281/zenodo.2554847