Triple

T12158921
Position Surface form Disambiguated ID Type / Status
Subject Hotat Bani Tamim Governorate E289652 entity
Predicate hasCulturalRegion P1968 FINISHED
Object Najd E44274 NE FINISHED

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: Najd | Statement: [Hotat Bani Tamim Governorate, hasCulturalRegion, Najd]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Najd
Context triple: [Hotat Bani Tamim Governorate, hasCulturalRegion, Najd]
  • A. Najd chosen
    Najd is the central plateau region of Saudi Arabia, historically known as a heartland of Arab tribal culture and the birthplace of the modern Saudi state.
  • B. Zau
    Zau is an ancient city, historically known as Sais, that served as an important religious and political center in Egypt’s Nile Delta.
  • C. Tayshet
    Tayshet is a town in Irkutsk Oblast, Russia, known as a major railway junction in Siberia.
  • D. Bayanhot
    Bayanhot is the administrative center and main urban settlement of Alxa League in western Inner Mongolia, China.
  • E. Nadym
    Nadym is a town in the Yamalo-Nenets Autonomous Okrug of Russia, known as a regional center for the natural gas industry and served by its own airport.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d6ab4c6710819097a9d228382dde43 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d915c277e481908351bf4e664dda42 completed April 10, 2026, 3:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f61e4c19248190913451db0a084172 completed May 2, 2026, 3:54 p.m.
Created at: April 8, 2026, 9:50 p.m.