Triple

T8079220
Position Surface form Disambiguated ID Type / Status
Subject Batangas E188572 entity
Predicate hasCity P316 FINISHED
Object Tanauan E432921 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: Tanauan | Statement: [Batangas, hasCity, Tanauan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tanauan
Context triple: [Batangas, hasCity, Tanauan]
  • A. Tanauan chosen
    Tanauan is a city in the Calabarzon region of the Philippines known for its growing industrial zones and proximity to Metro Manila.
  • B. Balamban
    Balamban is a coastal municipality in the province of Cebu in the Philippines, known for its shipbuilding industry and growing economic zone.
  • C. Bajo de Masinloc
    Bajo de Masinloc is a disputed South China Sea atoll, internationally known as Scarborough Shoal, claimed by both the Philippines and China for its strategic location and rich fishing grounds.
  • D. Danao
    Danao is a coastal city and municipality on Cebu Island in the Philippines known for its historical significance and local industries.
  • E. Daanbantayan
    Daanbantayan is a northern coastal municipality in the Philippine province of Cebu known as a gateway to popular diving and beach destinations like Malapascua Island.
  • 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.