Triple

T1333215
Position Surface form Disambiguated ID Type / Status
Subject Southern Thailand E28689 entity
Predicate hasProvince P285 FINISHED
Object Yala province E151102 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: Yala province | Statement: [Southern Thailand, hasProvince, Yala province]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yala province
Context triple: [Southern Thailand, hasProvince, Yala province]
  • A. Yala chosen
    Yala is a major city in Thailand’s deep south, known as an administrative, commercial, and cultural center near the Malaysian border.
  • B. Gela Sule
    Gela Sule is a variant name for Nggela Sule, a locality associated with the Nggela (Florida) Islands in the Solomon Islands.
  • C. Oriente Province
    Oriente Province was a former large administrative region in eastern Cuba that included major cities like Santiago de Cuba before being subdivided into smaller provinces in 1976.
  • D. Rif region
    The Rif region is a mountainous area in northern Morocco along the Mediterranean coast, known for its distinct Amazigh (Berber) culture and history of resistance.
  • E. Kutais Governorate
    Kutais Governorate was an administrative division of the Russian Empire in the Caucasus region, centered around the city of Kutaisi in what is now western Georgia.
  • 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_69a498561a508190a3e1bc137c2b866a completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c1e98900819092c54c0fb58b958a completed March 1, 2026, 10:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69acc62978c08190be285167cf579f9f completed March 8, 2026, 12:43 a.m.
Created at: March 1, 2026, 7:55 p.m.