Triple

T2520437
Position Surface form Disambiguated ID Type / Status
Subject EDSA E55508 entity
Predicate passesThrough P225 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: [EDSA, passesThrough, Taguig]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Taguig
Context triple: [EDSA, passesThrough, 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_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_69af9068798c8190958c5522276906fe completed March 10, 2026, 3:30 a.m.
Created at: March 6, 2026, 9:46 p.m.