Triple

T4242328
Position Surface form Disambiguated ID Type / Status
Subject Laguna de Bay E95441 entity
Predicate locatedNear P294 FINISHED
Object Muntinlupa E219900 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: Muntinlupa | Statement: [Laguna de Bay, locatedNear, Muntinlupa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Muntinlupa
Context triple: [Laguna de Bay, locatedNear, Muntinlupa]
  • A. Muntinlupa chosen
    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.
  • B. 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.
  • C. Mandaluyong
    Mandaluyong is a highly urbanized city in the Philippines known as part of Metro Manila’s central business and commercial district.
  • D. Antipolo
    Antipolo is a city in the province of Rizal, Philippines, known as a pilgrimage site and suburban residential area east of Metro Manila.
  • E. San Jose del Monte
    San Jose del Monte is a highly urbanized city in the Philippine province of Bulacan, known for its large residential communities and role as a suburban extension of Metro Manila.
  • 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_69b3453d91548190b4d4ef8fe52aa2ac completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34e891bc08190831187da4f553f48 completed March 12, 2026, 11:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69b627c8265881908a9bfdb032389151 completed March 15, 2026, 3:30 a.m.
Created at: March 12, 2026, 11:05 p.m.