Triple

T17960867
Position Surface form Disambiguated ID Type / Status
Subject Tahir E449076 entity
Predicate hasVariantTransliteration P5923 FINISHED
Object Tahirr NE NERFINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Tahirr | Statement: [Tahir, hasVariantTransliteration, Tahirr]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tahirr
Context triple: [Tahir, hasVariantTransliteration, Tahirr]
  • A. Tahir chosen
    Tahir is a common Arabic-origin surname used by various notable individuals across the Muslim world and diaspora.
  • B. Taha
    Taha is a family name most notably associated with Mahmoud Mohammed Taha, a prominent Sudanese Islamic reformer and thinker.
  • C. Dhahir
    Dhahir is a city located in Yemen's Saada region, known for its position in the country's mountainous northern area.
  • D. Tahsin
    Tahsin is a masculine given name of Turkish and Arabic origin, commonly used in Turkey and other Muslim-majority countries.
  • E. Hasana
    Hasana is a small town in Egypt’s North Sinai Governorate, situated in the Sinai Peninsula.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d8b9f8cca8819099836916c56b7c95 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e4b131fa8481908cd756f350eb6359 completed April 19, 2026, 10:40 a.m.
Created at: April 10, 2026, 10:22 a.m.