Triple

T17306149
Position Surface form Disambiguated ID Type / Status
Subject Masyaf E420168 entity
Predicate locatedIn P40 FINISHED
Object Hama Governorate 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: Hama Governorate | Statement: [Masyaf, locatedIn, Hama Governorate]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hama Governorate
Context triple: [Masyaf, locatedIn, Hama Governorate]
  • A. Hama Governorate chosen
    Hama Governorate is an administrative region in west-central Syria known for its agricultural production and the historic city of Hama as its capital.
  • B. Afif Governorate
    Afif Governorate is an administrative region in central Saudi Arabia known for its desert landscapes and location within the broader Riyadh area.
  • C. Wasit Governorate
    Wasit Governorate is an administrative region in eastern Iraq known for its agricultural lands along the Tigris River and its capital city, Kut.
  • D. Beheira Governorate
    Beheira Governorate is an administrative region in northern Egypt, situated in the Nile Delta and known for its agricultural productivity and Mediterranean coastline.
  • E. Sabya Governorate
    Sabya Governorate is an administrative division in Saudi Arabia’s Jizan Region, centered around the city of Sabya and known for its agricultural activity and growing urban population.
  • 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_69d889d22b848190a4663d0b8f8f76e7 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e438ff3ee08190ab4c44a22f86b38b completed April 19, 2026, 2:07 a.m.
Created at: April 10, 2026, 5:43 a.m.