Triple

T2369952
Position Surface form Disambiguated ID Type / Status
Subject Pasig River E46063 entity
Predicate flowsThrough P225 FINISHED
Object Mandaluyong E210936 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: Mandaluyong | Statement: [Pasig River, flowsThrough, Mandaluyong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mandaluyong
Context triple: [Pasig River, flowsThrough, Mandaluyong]
  • A. Mandaluyong chosen
    Mandaluyong is a highly urbanized city in the Philippines known as part of Metro Manila’s central business and commercial district.
  • B. 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.
  • C. Caloocan
    Caloocan is a highly urbanized city in the Philippines that forms part of the northern section of Metro Manila and serves as a major residential and commercial hub.
  • D. 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.
  • E. Marikina
    Marikina is a highly urbanized city in the Philippines known as the "Shoe Capital of the Philippines" for its long-standing shoe-making industry and is part of the Metro Manila region.
  • 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_69abc76f5aec8190867d621e6849258c completed March 7, 2026, 6:36 a.m.
NED1 Entity disambiguation (via context triple) batch_69af1776d8d08190a7aae0969019d8f7 completed March 9, 2026, 6:54 p.m.
Created at: March 4, 2026, 7:56 p.m.