Triple

T800877
Position Surface form Disambiguated ID Type / Status
Subject Luzon E17124 entity
Predicate containsCity P294 FINISHED
Object Caloocan E36022 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: Caloocan | Statement: [Luzon, containsCity, Caloocan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Caloocan
Context triple: [Luzon, containsCity, Caloocan]
  • A. Quezon City
    Quezon City is a major urban center in Metro Manila known for hosting many national government institutions, universities, and media networks in the Philippines.
  • B. Cavite
    Cavite is a coastal province in the Calabarzon region of the Philippines, historically significant as a center of the Philippine Revolution and located just south of Metro Manila.
  • C. Baguio
    Baguio is a mountain resort city in the Philippines known for its cool climate, pine forests, and role as the country's "Summer Capital."
  • D. Metro Manila chosen
    Metro Manila is the densely populated national capital region of the Philippines, encompassing Manila and several surrounding cities as the country’s political, economic, and cultural center.
  • E. Tarlac
    Tarlac is a landlocked province in the Central Luzon region of the Philippines known for its culturally diverse population and agricultural economy.
  • 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_69a49378b9c48190adbf5f62e5b7aca1 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a7cc75e88190bd35aabe51051b51 completed March 1, 2026, 8:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7b83f0fb4819097f29c9ab90cf1a8 completed March 4, 2026, 4:42 a.m.
Created at: March 1, 2026, 7:38 p.m.