Triple

T4122523
Position Surface form Disambiguated ID Type / Status
Subject Cebu Island E92646 entity
Predicate hasCity P316 FINISHED
Object Talisay City E364591 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: Talisay City | Statement: [Cebu Island, hasCity, Talisay City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Talisay City
Context triple: [Cebu Island, hasCity, Talisay City]
  • A. Talisay City chosen
    Talisay City is a coastal component city in the province of Cebu in the Philippines, known for its historical significance and proximity to Metro Cebu.
  • B. Talisay
    Talisay is a city in the Philippine province of Negros Occidental known for its sugarcane industry and historical landmarks.
  • C. Legazpi City
    Legazpi City is a coastal city in the Philippines known as the regional center of the Bicol Region and famed for its views of the Mayon Volcano.
  • D. Masbate City
    Masbate City is a coastal component city and the capital of Masbate Province in the Philippines, known as a commercial and administrative center in the Bicol Region.
  • E. Palayan City
    Palayan City is a planned component city in the Philippines known for serving as the administrative and governmental center of the province of Nueva Ecija.
  • 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_69aed9685f70819086932777aec8d959 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69af020728a08190a50a16b40690cbce completed March 9, 2026, 5:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69be6f845ce48190a5feae21980530d6 completed March 21, 2026, 10:14 a.m.
Created at: March 9, 2026, 3:41 p.m.