Triple

T2369973
Position Surface form Disambiguated ID Type / Status
Subject Pasig River E46063 entity
Predicate cityOnBank P7935 FINISHED
Object Taguig E104725 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: Taguig | Statement: [Pasig River, cityOnBank, Taguig]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Taguig
Context triple: [Pasig River, cityOnBank, Taguig]
  • A. Taguig chosen
    Taguig is a highly urbanized city in Metro Manila in the Philippines, known for the Bonifacio Global City (BGC) business district and rapid commercial and residential development.
  • B. Malabon
    Malabon is a coastal city in the northern part of Metro Manila in the Philippines, known for its historic districts, flood-prone waterways, and distinctive local cuisine.
  • C. Muntinlupa
    Muntinlupa is a highly urbanized city in the southern part of Metro Manila in the Philippines, known for housing the New Bilibid Prison and major commercial and residential developments like Alabang.
  • D. Mandaluyong
    Mandaluyong is a highly urbanized city in the Philippines known as part of Metro Manila’s central business and commercial district.
  • E. Bacoor
    Bacoor is a coastal city in the province of Cavite in the Philippines, situated just south of Metro Manila along the shores of Manila Bay.
  • 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_69a88a145268819083e2736cb835c696 completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abd0d813dc8190aa331cdca0b75eca completed March 7, 2026, 7:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69af1f7ac4c8819091132fa9cb265552 completed March 9, 2026, 7:28 p.m.
Created at: March 4, 2026, 7:56 p.m.