Triple

T807495
Position Surface form Disambiguated ID Type / Status
Subject Visayas E17470 entity
Predicate language P15 FINISHED
Object Kinaray-a E58819 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: Kinaray-a | Statement: [Visayas, language, Kinaray-a]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kinaray-a
Context triple: [Visayas, language, Kinaray-a]
  • A. Ilonggo chosen
    Ilonggo is a major Austronesian language spoken primarily in Western Visayas and parts of Mindanao in the Philippines.
  • B. Batabanó
    Batabanó is a coastal municipality in western Cuba known for its fishing industry and ferry connections to nearby islands.
  • C. Amánung Kapampángan
    Amánung Kapampángan is the endonym for the Kapampangan language spoken primarily in the Pampanga region of the Philippines.
  • D. Kumina
    Kumina is a Jamaican Afro-Caribbean spiritual tradition and performance practice rooted in Central African (Kongo) heritage, known for its drumming, dancing, and ancestral spirit possession rituals.
  • 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_69a4937ae8a08190b5084a03d532b30e completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4ab23862c8190bfd6558936c58410 completed March 1, 2026, 9:09 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.