Triple

T11135815
Position Surface form Disambiguated ID Type / Status
Subject Yucatán E263405 entity
Predicate contains P35 FINISHED
Object Celestún E228421 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: Celestún | Statement: [Yucatán, contains, Celestún]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Celestún
Context triple: [Yucatán, contains, Celestún]
  • A. Celestún chosen
    Celestún is a small coastal town in the Mexican state of Yucatán, known for its beaches, fishing community, and as a gateway to nearby flamingo-filled wetlands and nature reserves.
  • B. Urana
    Urana is a small rural town in the Riverina region of New South Wales, Australia, known for its agricultural surroundings and historic country character.
  • C. Planá
    Planá is a town in the Plzeň Region of the Czech Republic that serves as a local administrative and service center for surrounding municipalities.
  • D. Caála
    Caála is a town and municipality in Angola’s Huambo Province, known as an important regional agricultural and transport hub on the central plateau.
  • E. Areora
    Areora is a small village on the island of Mauke in the Cook Islands, known for its traditional Polynesian community and rural setting.
  • 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_69d6aa9c0ba08190bbd19c217489b755 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e85daddc8190a1ae2a4a75cc8d50 completed April 9, 2026, 5:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69e441fa286881909a8279a8ea6944e7 completed April 19, 2026, 2:46 a.m.
Created at: April 8, 2026, 9:28 p.m.