Triple

T10687495
Position Surface form Disambiguated ID Type / Status
Subject Philippine Austronesian languages E251916 entity
Predicate hasMember P10 FINISHED
Object Ibanag E101548 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: Ibanag | Statement: [Philippine Austronesian languages, hasMember, Ibanag]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ibanag
Context triple: [Philippine Austronesian languages, hasMember, Ibanag]
  • A. Ibanag chosen
    Ibanag is an Austronesian language spoken primarily in the Cagayan Valley region of northern Luzon in the Philippines.
  • B. Kapampangan
    Kapampangan is an Austronesian language spoken primarily in the Pampanga region of the Philippines by the Kapampangan ethnic group.
  • C. Aguiguan
    Aguiguan is a small, uninhabited island in the Northern Mariana Islands known for its rugged terrain and seabird colonies.
  • D. Yakan
    Yakan is an Austronesian language spoken primarily by the Yakan people of Basilan and nearby areas in the southern Philippines.
  • E. Sugbuanon
    Sugbuanon refers to the Cebuano people, a Visayan ethnolinguistic group from the central and southern Philippines known for speaking the Cebuano language.
  • 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_69d6aa5bd7c08190a816e733b4045c23 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fd19f0f481909eeaa75d17d9c060 completed April 9, 2026, 1:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69d998c6fb4881908a8e13912c405ec8 completed April 11, 2026, 12:41 a.m.
Created at: April 8, 2026, 9:10 p.m.