From Networks to Named Entities and Back Again: Exploring Classical Arabic Isnad Networks
This paper explores new methods for disambiguating the identity of individuals in classical Arabic citations (isnāds) using a network-based approach. After training a model to extract name mentions from classical Arabic, we embed these mentions in vector space using fine-tuned BERT representations a...
| Nebentitel: | Mit arabischen Schriftzeichen im Text |
|---|---|
| VerfasserInnen: | ; ; |
| Medienart: | Elektronisch Aufsatz |
| Sprache: | Englisch |
| Verfügbarkeit prüfen: | HBZ Gateway |
| Journals Online & Print: | Lade...
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| Fernleihe: | Fernleihe für die Fachinformationsdienste |
| Veröffentlicht: |
Université du Luxembourg
2023
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| In: |
Journal of historical network research
Jahr: 2023, Band: 8, Seiten: 1-20 |
| weitere Schlagwörter: | B
Hadith
B name disambiguation B Natural Language Processing B Network Analysis |
| Online Zugang: |
Volltext (kostenfrei) Volltext (kostenfrei) |
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| 520 | |a This paper explores new methods for disambiguating the identity of individuals in classical Arabic citations (isnāds) using a network-based approach. After training a model to extract name mentions from classical Arabic, we embed these mentions in vector space using fine-tuned BERT representations and use community detection to infer clusters of coreferent mentions. The best-performing clustering approach reduces error on the CoNLL metric by 30%. Then, as a case study, we examine the problem of determining the number of direct transmitters to Ibn ʿAsākir (d. 1176) in a set of isnāds taken from the 12th century historical text Taʾrīkh Madīnat Dimashq (TMD, History of Damascus), using our method to replicate human judgement. | ||
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