Triple

T8079221
Position Surface form Disambiguated ID Type / Status
Subject Batangas E188572 entity
Predicate hasMunicipality P847 FINISHED
Object Taal E99105 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 | Statement: [Batangas, hasMunicipality, Taal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Taal
Context triple: [Batangas, hasMunicipality, Taal]
  • A. Taal
    Taal is a 1999 Indian musical romantic drama film renowned for its acclaimed soundtrack composed by A. R. Rahman.
  • B. Taal Lake
    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. Taal Volcano chosen
    Taal Volcano is an active and historically explosive volcano in the Philippines, famous for its picturesque crater lake setting on the island of Luzon.
  • D. Kanlaon Volcano
    Kanlaon Volcano is an active stratovolcano and one of the most prominent volcanic peaks in the central Philippines, located on Negros Island.
  • E. Bulusan Volcano
    Bulusan Volcano is an active stratovolcano in Sorsogon province on the island of Luzon in the Philippines, known for its frequent phreatic eruptions and associated hazards.
  • 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_69ca82b50c708190863f661d438e68df completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb40a3f01c819096a2c9d5d5199fe6 completed March 31, 2026, 3:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc63f79ac08190af49e77bee67921d completed April 1, 2026, 12:16 a.m.
Created at: March 30, 2026, 5:28 p.m.