Triple

T21512366
Position Surface form Disambiguated ID Type / Status
Subject Fort of Gao E530758 entity
Predicate locatedIn P40 FINISHED
Object Gao Region 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: Gao Region | Statement: [Fort of Gao, locatedIn, Gao Region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gao Region
Context triple: [Fort of Gao, locatedIn, Gao Region]
  • A. Gao Region chosen
    Gao Region is a strategic area in northern Mali that has been a focal point of military operations and conflict, particularly during the French-led intervention against Islamist militants.
  • B. Huari Province
    Huari Province is an administrative division in the Ancash Region of central Peru, known for encompassing the important archaeological site of Chavín de Huántar.
  • C. Bié Province
    Bié Province is a central Angolan province known for its highland terrain, agricultural activity, and strategic location bordering several other provinces.
  • D. Sanma Province
    Sanma Province is an administrative region in northern Vanuatu that includes the country’s largest island, Espiritu Santo, and its surrounding islands.
  • E. Yaodu District
    Yaodu District is the central urban district and administrative heart of Linfen City in Shanxi Province, China.
  • 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_69e0c45c81f08190a6b8bbb70a45aae7 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e9ea8779c081908171c58d345d54ae completed April 23, 2026, 9:46 a.m.
Created at: April 16, 2026, 6:25 p.m.