Triple

T20001958
Position Surface form Disambiguated ID Type / Status
Subject Tayabas E494352 entity
Predicate nearbyMunicipality P4647 FINISHED
Object Lucban E722476 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: Lucban | Statement: [Tayabas, nearbyMunicipality, Lucban]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lucban
Context triple: [Tayabas, nearbyMunicipality, Lucban]
  • A. Lucban chosen
    Lucban is a municipality in the province of Quezon in the Philippines, known for its colorful Pahiyas Festival and production of longganisa and other local delicacies.
  • B. Capampangan
    Capampangan is an Austronesian language spoken primarily in the Pampanga region of the Philippines by the Kapampangan people.
  • C. Balamban
    Balamban is a coastal municipality in the province of Cebu in the Philippines, known for its shipbuilding industry and growing economic zone.
  • D. Gorospe
    Gorospe is a Basque surname most notably associated with Spanish former professional cyclist Julián Gorospe.
  • E. Lukbán
    Lukbán is a Filipino surname most notably associated with Vicente Lukbán, a revolutionary general and leader during the Philippine struggle against Spanish and American colonial rule.
  • 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_69da626b2d748190886981ea90c8b2ea completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e661a222908190b88e1d11cb1b7ee3 completed April 20, 2026, 5:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a08050bb1fc81908b9ce173babdd256 completed May 16, 2026, 5:47 a.m.
Created at: April 11, 2026, 3:32 p.m.