span-marker-xlm-roberta-base-fewnerd-fine-super Open-source Model - Supports Multilingual Named Entity Recognition

Span Marker Xlm Roberta Base Fewnerd Fine Super

Developed by tomaarsen

This is a SpanMarker model trained on the FewNERD dataset for multilingual named entity recognition tasks, based on the xlm-roberta-base encoder.

Sequence Labeling #Multilingual Entity Recognition #Fine-grained NER #Cross-domain Entity Extraction

Downloads 148

Release Time : 6/15/2023

Model Overview

This model uses the SpanMarker architecture, specifically designed for named entity recognition (NER) tasks, supporting English and multilingual text processing.

Model Features

Multilingual Support

Based on the xlm-roberta-base encoder, supporting English and multilingual text processing

Fine-grained Entity Recognition

Capable of recognizing 66 different types of entities, including art, architecture, events, locations, organizations, etc.

SpanMarker Architecture

Adopts the SpanMarker architecture, specifically optimized for named entity recognition tasks

Model Capabilities

Named Entity Recognition

Multilingual Text Processing

Fine-grained Entity Classification

Use Cases

Information Extraction

Entity Recognition in News Articles

Extract entities such as person names, place names, and organization names from news articles

F1 score 0.6885

Academic Literature Analysis

Identify professional entities such as chemical substances and biological terms in scientific research papers

F1 score for chemical substances 0.5832, F1 score for biological terms 0.6497

Business Intelligence

Company Name Recognition

Extract company names and organization information from business documents

F1 score 0.6917

Product Recognition

Identify product names and types mentioned in the text

F1 score for automobile products 0.7234, F1 score for aircraft products 0.6464

🚀 SpanMarker with xlm-roberta-base on FewNERD

This is a SpanMarker model trained on the FewNERD dataset, which can be used for Named Entity Recognition. This SpanMarker model uses xlm-roberta-base as the underlying encoder.

📚 Documentation

Model Details

Model Information

Property	Details
Model Type	SpanMarker
Encoder	xlm-roberta-base
Maximum Sequence Length	256 tokens
Maximum Entity Length	8 words
Training Dataset	FewNERD
Languages	en, multilingual
License	cc-by-sa-4.0

Model Sources

Repository: SpanMarker on GitHub
Thesis: SpanMarker For Named Entity Recognition

Model Labels

Label	Examples
art-broadcastprogram	"The Gale Storm Show : Oh , Susanna", "Corazones", "Street Cents"
art-film	"L'Atlantide", "Shawshank Redemption", "Bosch"
art-music	"Hollywood Studio Symphony", "Atkinson , Danko and Ford ( with Brockie and Hilton )", "Champion Lover"
art-other	"Venus de Milo", "Aphrodite of Milos", "The Today Show"
art-painting	"Cofiwch Dryweryn", "Production/Reproduction", "Touit"
art-writtenart	"The Seven Year Itch", "Time", "Imelda de ' Lambertazzi"
building-airport	"Newark Liberty International Airport", "Luton Airport", "Sheremetyevo International Airport"
building-hospital	"Hokkaido University Hospital", "Yeungnam University Hospital", "Memorial Sloan-Kettering Cancer Center"
building-hotel	"Radisson Blu Sea Plaza Hotel", "The Standard Hotel", "Flamingo Hotel"
building-library	"British Library", "Berlin State Library", "Bayerische Staatsbibliothek"
building-other	"Communiplex", "Henry Ford Museum", "Alpha Recording Studios"
building-restaurant	"Fatburger", "Carnegie Deli", "Trumbull"
building-sportsfacility	"Boston Garden", "Glenn Warner Soccer Facility", "Sports Center"
building-theater	"Pittsburgh Civic Light Opera", "National Paris Opera", "Sanders Theatre"
event-attack/battle/war/militaryconflict	"Jurist", "Easter Offensive", "Vietnam War"
event-disaster	"1693 Sicily earthquake", "1990s North Korean famine", "the 1912 North Mount Lyell Disaster"
event-election	"March 1898 elections", "Elections to the European Parliament", "1982 Mitcham and Morden by-election"
event-other	"Eastwood Scoring Stage", "Union for a Popular Movement", "Masaryk Democratic Movement"
event-protest	"Russian Revolution", "French Revolution", "Iranian Constitutional Revolution"
event-sportsevent	"World Cup", "Stanley Cup", "National Champions"
location-GPE	"Mediterranean Basin", "Croatian", "the Republic of Croatia"
location-bodiesofwater	"Norfolk coast", "Atat√ºrk Dam Lake", "Arthur Kill"
location-island	"Laccadives", "Staten Island", "new Samsat district"
location-mountain	"Ruweisat Ridge", "Miteirya Ridge", "Salamander Glacier"
location-other	"Victoria line", "Northern City Line", "Cartuther"
location-park	"Painted Desert Community Complex Historic District", "Shenandoah National Park", "Gramercy Park"
location-road/railway/highway/transit	"Newark-Elizabeth Rail Link", "NJT", "Friern Barnet Road"
organization-company	"Church 's Chicken", "Texas Chicken", "Dixy Chicken"
organization-education	"MIT", "Belfast Royal Academy and the Ulster College of Physical Education", "Barnard College"
organization-government/governmentagency	"Congregazione dei Nobili", "Diet", "Supreme Court"
organization-media/newspaper	"TimeOut Melbourne", "Al Jazeera", "Clash"
organization-other	"IAEA", "4th Army", "Defence Sector C"
organization-politicalparty	"Al Wafa ' Islamic", "Shimpot≈ç", "Kenseit≈ç"
organization-religion	"UPCUSA", "Jewish", "Christian"
organization-showorganization	"Bochumer Symphoniker", "Mr. Mister", "Lizzy"
organization-sportsleague	"First Division", "NHL", "China League One"
organization-sportsteam	"Tottenham", "Arsenal", "Luc Alphand Aventures"
other-astronomything	"Algol", "Zodiac", "`` Caput Larvae ''"
other-award	"Grand Commander of the Order of the Niger", "Order of the Republic of Guinea and Nigeria", "GCON"
other-biologything	"Amphiphysin", "BAR", "N-terminal lipid"
other-chemicalthing	"carbon dioxide", "sulfur", "uranium"
other-currency	"$", "lac crore", "Travancore Rupee"
other-disease	"hypothyroidism", "bladder cancer", "French Dysentery Epidemic of 1779"
other-educationaldegree	"Master", "Bachelor", "BSc ( Hons ) in physics"
other-god	"El", "Fujin", "Raijin"
other-language	"Breton-speaking", "Latin", "English"
other-law	"United States Freedom Support Act", "Thirty Years ' Peace", "Leahy‚ÄìSmith America Invents Act ( AIA"
other-livingthing	"insects", "patchouli", "monkeys"
other-medical	"amitriptyline", "pediatrician", "Pediatrics"
person-actor	"Tch√©ky Karyo", "Edmund Payne", "Ellaline Terriss"
person-artist/author	"George Axelrod", "Hicks", "Gaetano Donizett"
person-athlete	"Jaguar", "Neville", "Tozawa"
person-director	"Richard Quine", "Frank Darabont", "Bob Swaim"
person-other	"Campbell", "Richard Benson", "Holden"
person-politician	"Rivi√®re", "Emeric", "William"
person-scholar	"Stedman", "Wurdack", "Stalmine"
person-soldier	"Joachim Ziegler", "Krukenberg", "Helmuth Weidling"
product-airplane	"EC135T2 CPDS", "Spey-equipped FGR.2s", "Luton"
product-car	"Phantom", "Corvettes - GT1 C6R", "100EX"
product-food	"V. labrusca", "red grape", "yakiniku"
product-game	"Hardcore RPG", "Airforce Delta", "Splinter Cell"
product-other	"PDP-1", "Fairbottom Bobs", "X11"
product-ship	"Essex", "Congress", "HMS `` Chinkara ''"
product-software	"Wikipedia", "Apdf", "AmiPDF"
product-train	"55022", "Royal Scots Grey", "High Speed Trains"
product-weapon	"AR-15 's", "ZU-23-2MR Wr√≥bel II", "ZU-23-2M Wr√≥bel"

Evaluation

Metrics

Label	Precision	Recall	F1
all	0.6890	0.6879	0.6885
art-broadcastprogram	0.6	0.5771	0.5883
art-film	0.7384	0.7453	0.7419
art-music	0.7930	0.7221	0.7558
art-other	0.4245	0.2900	0.3446
art-painting	0.5476	0.4035	0.4646
art-writtenart	0.6400	0.6539	0.6469
building-airport	0.8219	0.8242	0.8230
building-hospital	0.7024	0.8104	0.7526
building-hotel	0.7175	0.7283	0.7228
building-library	0.74	0.7296	0.7348
building-other	0.5828	0.5910	0.5869
building-restaurant	0.5525	0.5216	0.5366
building-sportsfacility	0.6187	0.7881	0.6932
building-theater	0.7067	0.7626	0.7336
event-attack/battle/war/militaryconflict	0.7544	0.7468	0.7506
event-disaster	0.5882	0.5314	0.5584
event-election	0.4167	0.2198	0.2878
event-other	0.4902	0.4042	0.4430
event-protest	0.3643	0.2831	0.3186
event-sportsevent	0.6125	0.6239	0.6182
location-GPE	0.8102	0.8553	0.8321
location-bodiesofwater	0.6888	0.7725	0.7282
location-island	0.7285	0.6440	0.6836
location-mountain	0.7129	0.7327	0.7227
location-other	0.4376	0.2560	0.3231
location-park	0.6991	0.6900	0.6945
location-road/railway/highway/transit	0.6936	0.7259	0.7094
organization-company	0.6921	0.6912	0.6917
organization-education	0.7838	0.7963	0.7900
organization-government/governmentagency	0.5363	0.4394	0.4831
organization-media/newspaper	0.6215	0.6705	0.6451
organization-other	0.5766	0.5157	0.5444
organization-politicalparty	0.6449	0.7324	0.6859
organization-religion	0.5139	0.6057	0.5560
organization-showorganization	0.5620	0.5657	0.5638
organization-sportsleague	0.6348	0.6542	0.6443
organization-sportsteam	0.7138	0.7566	0.7346
other-astronomything	0.7418	0.7625	0.752
other-award	0.7291	0.6736	0.7002
other-biologything	0.6735	0.6275	0.6497
other-chemicalthing	0.6025	0.5651	0.5832
other-currency	0.6843	0.8411	0.7546
other-disease	0.6284	0.7089	0.6662
other-educationaldegree	0.5856	0.6033	0.5943
other-god	0.6089	0.6913	0.6475
other-language	0.6608	0.7968	0.7225
other-law	0.6693	0.7246	0.6958
other-livingthing	0.6070	0.6014	0.6042
other-medical	0.5062	0.5113	0.5088
person-actor	0.8274	0.7673	0.7962
person-artist/author	0.6761	0.7294	0.7018
person-athlete	0.8132	0.8347	0.8238
person-director	0.675	0.6823	0.6786
person-other	0.6472	0.6388	0.6429
person-politician	0.6621	0.6593	0.6607
person-scholar	0.5181	0.5007	0.5092
person-soldier	0.4750	0.5131	0.4933
product-airplane	0.6230	0.6717	0.6464
product-car	0.7293	0.7176	0.7234

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