Triple

T16958795
Position Surface form Disambiguated ID Type / Status
Subject Bahay na bato E411373 entity
Predicate typicalLocation P3231 FINISHED
Object Taal, Batangas E101546 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: Taal, Batangas | Statement: [Bahay na bato, typicalLocation, Taal, Batangas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Taal, Batangas
Context triple: [Bahay na bato, typicalLocation, Taal, Batangas]
  • A. Taal
    Taal is a 1999 Indian musical romantic drama film renowned for its acclaimed soundtrack composed by A. R. Rahman.
  • B. Taal Lake chosen
    Taal Lake is a large volcanic lake in the Philippines known for containing Taal Volcano, one of the country’s most active and picturesque volcanoes.
  • C. Calatagan
    Calatagan is a coastal municipality in the province of Batangas in the Philippines, known for its beaches, diving spots, and historical sites.
  • D. Tinio
    Tinio is a Filipino surname most notably associated with Manuel Tinio, a prominent general of the Philippine Revolution and early 20th-century political figure.
  • E. Maljamar
    Maljamar is a small unincorporated community in southeastern New Mexico known historically for its oil and gas activity.
  • 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_69d886c9c9d481909afe222093641cae completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d01e420881909be1d93d7d6772fd completed April 18, 2026, 6:40 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00d468f5048190aa43b212ec7a7306 completed May 10, 2026, 6:54 p.m.
Created at: April 10, 2026, 5:31 a.m.