Triple

T12083873
Position Surface form Disambiguated ID Type / Status
Subject Antipolo E287754 entity
Predicate isPartOf P10 FINISHED
Object Calabarzon E97442 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: Calabarzon | Statement: [Antipolo, isPartOf, Calabarzon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Calabarzon
Context triple: [Antipolo, isPartOf, Calabarzon]
  • A. Calabarzon chosen
    Calabarzon is a populous and industrialized region in the southern part of Luzon in the Philippines, known for its mix of urban centers, agricultural areas, and manufacturing hubs.
  • B. Tagbina
    Tagbina is a rural municipality in the province of Surigao del Sur in the Caraga region of Mindanao, Philippines.
  • C. Aguiguan
    Aguiguan is a small, uninhabited island in the Northern Mariana Islands known for its rugged terrain and seabird colonies.
  • D. Bucoda
    Bucoda is a small town in Thurston County, Washington, known for its historic coal-mining roots and its claim as the "World's Tiniest Town with the Biggest Halloween Spirit."
  • E. Ibanag
    Ibanag is an Austronesian language spoken primarily in the Cagayan Valley region of northern Luzon in the Philippines.
  • 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_69d6ab4964708190850585628b287b0c completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d91513bbb0819084a8bb877e03060c completed April 10, 2026, 3:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69f62a7c2b0081909994ea88683a39f4 completed May 2, 2026, 4:46 p.m.
Created at: April 8, 2026, 9:48 p.m.