Triple

T4636585
Position Surface form Disambiguated ID Type / Status
Subject Taal Lake E101546 entity
Predicate nearCity P350 FINISHED
Object Talisay, Batangas E442866 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, Batangas | Statement: [Taal Lake, nearCity, Talisay, Batangas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Talisay, Batangas
Context triple: [Taal Lake, nearCity, Talisay, Batangas]
  • A. Talisay, Batangas chosen
    Talisay, Batangas is a lakeside municipality in the Philippines known as a primary gateway to Taal Volcano and its scenic crater lake.
  • B. Talisay City
    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.
  • C. 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.
  • D. Calamba, Laguna
    Calamba, Laguna is a highly urbanized city in the Philippines known as the hometown of national hero José Rizal and a major industrial and commercial hub in the Calabarzon region.
  • E. Talisay
    Talisay is a city in the Philippine province of Negros Occidental known for its sugarcane industry and historical landmarks.
  • 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_69bd43d2f1c081908cd4b7ec48ecc73d completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5a62a9e48190b0cf1cbcc51f00c0 completed March 20, 2026, 2:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfacba5fc8190bc86157ee5719ced completed March 21, 2026, 1:56 a.m.
Created at: March 20, 2026, 1:13 p.m.