Triple

T2520434
Position Surface form Disambiguated ID Type / Status
Subject EDSA E55508 entity
Predicate passesThrough 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: [EDSA, passesThrough, Mandaluyong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mandaluyong
Context triple: [EDSA, passesThrough, 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_69ab49e4749c8190813311efd1630f1b completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd2343e3081908819dc58d8ff40ce completed March 7, 2026, 7:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69af83921d3481909f7bf43b3300056c completed March 10, 2026, 2:36 a.m.
Created at: March 6, 2026, 9:46 p.m.