Triple

T9724795
Position Surface form Disambiguated ID Type / Status
Subject Villa Clara Province E235578 entity
Predicate containsCity P294 FINISHED
Object Camajuaní E818442 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: Camajuaní | Statement: [Villa Clara Province, containsCity, Camajuaní]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Camajuaní
Context triple: [Villa Clara Province, containsCity, Camajuaní]
  • A. Camajuaní chosen
    Camajuaní is a municipality in central Cuba known for its agricultural economy and location within Villa Clara Province.
  • B. Comayagüela
    Comayagüela is a major urban district of Honduras that, together with Tegucigalpa, forms the country’s capital area.
  • C. Pacasmayo
    Pacasmayo is a coastal city in northern Peru known for its long pier, surfing beaches, and colonial-era architecture.
  • D. Chiriguaná
    Chiriguaná is a municipality and town in northern Colombia’s Cesar Department, known for its agricultural economy and location along key transport routes in the Caribbean region.
  • E. Acawayo
    Acawayo is an alternative name for the Akawaio language, an indigenous Cariban language spoken by the Akawaio people of northern South America.
  • 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_69ca84d0fad481909cdd45aa77416c48 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9e7838448190a7b5b259765a0d95 completed April 1, 2026, 10:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1c40575f48190807b6a3f10e63b41 completed April 5, 2026, 2:08 a.m.
Created at: March 30, 2026, 8:21 p.m.