Triple

T17018873
Position Surface form Disambiguated ID Type / Status
Subject Tanauan, Batangas E412891 entity
Predicate locatedIn P40 FINISHED
Object Batangas NE NERFINISHED

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: Batangas | Statement: [Tanauan, Batangas, locatedIn, Batangas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Batangas
Context triple: [Tanauan, Batangas, locatedIn, Batangas]
  • A. Batangas chosen
    Batangas is a province in the Calabarzon region of the Philippines known for its beaches, diving spots, and the Taal Volcano.
  • B. Camarines Sur
    Camarines Sur is a province in the Bicol Region of the Philippines known for its rich Bikolano culture, religious heritage sites, and natural attractions such as lakes, mountains, and eco-tourism destinations.
  • C. Pampanga
    Pampanga is a province in the Central Luzon region of the Philippines, known for its rich culinary heritage, vibrant festivals, and significant role in the country’s history and culture.
  • D. Zambales
    Zambales is a coastal province in the Central Luzon region of the Philippines, known for its beaches, mangoes, and ethnolinguistic diversity.
  • E. Batangas City
    Batangas City is a major port and industrial hub in the province of Batangas in the Philippines, known for its oil refineries, commercial activity, and role as a gateway to nearby islands.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d886cc4170819093deddc7b8b4b6a7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d481a0988190a13d0928e0c7ebbf completed April 18, 2026, 6:59 p.m.
Created at: April 10, 2026, 5:33 a.m.