Triple

T12504988
Position Surface form Disambiguated ID Type / Status
Subject Gaddang E298923 entity
Predicate relatedGroup P37 FINISHED
Object Itawit E336294 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: Itawit | Statement: [Gaddang, relatedGroup, Itawit]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Itawit
Context triple: [Gaddang, relatedGroup, Itawit]
  • A. Itawit chosen
    Itawit is an Austronesian language spoken by the Itawit people primarily in the Cagayan Valley region of northern Luzon in the Philippines.
  • B. Itaitinga
    Itaitinga is a municipality in the state of Ceará in northeastern Brazil, located in the metropolitan region of Fortaleza.
  • C. Iguig
    Iguig is a municipality in the province of Cagayan in the Philippines, known for its historic churches and scenic riverside landscapes.
  • D. Itatiaia
    Itatiaia is a municipality in the state of Rio de Janeiro, Brazil, best known for the nearby Itatiaia National Park, one of the country’s oldest and most important protected natural areas.
  • E. Tubigon
    Tubigon is a coastal municipality in the Philippine province of Bohol, known as a busy port town and gateway to nearby islands such as Cebu.
  • 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_69d6ada4cd388190ae3bbf83ff87057a completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94dfddf38819099263b8b1e804736 completed April 10, 2026, 7:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f65eac74608190a6f1941ed5a05212 completed May 2, 2026, 8:29 p.m.
Created at: April 8, 2026, 9:57 p.m.