Triple

T9483426
Position Surface form Disambiguated ID Type / Status
Subject Boholano E228701 entity
Predicate hasAlternativeName P39 FINISHED
Object Boholano Binisaya E45639 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: Boholano Binisaya | Statement: [Boholano, hasAlternativeName, Boholano Binisaya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Boholano Binisaya
Context triple: [Boholano, hasAlternativeName, Boholano Binisaya]
  • A. Binisaya chosen
    Binisaya is a major Austronesian language of the Philippines, widely spoken in the Central Visayas and parts of Mindanao.
  • B. Masbateño Bisaya
    Masbateño Bisaya is a Visayan language variety spoken primarily on Masbate Island in the Philippines, influenced by both Cebuano and Hiligaynon.
  • C. Tagalog
    Tagalog is an Austronesian language primarily spoken in the Philippines and serves as the basis for the country’s national language, Filipino.
  • D. Bikol language
    The Bikol language is an Austronesian language spoken primarily in the Bicol Region of the Philippines, known for its several regional varieties and close relation to other Central Philippine languages.
  • E. Kapampangan language
    Kapampangan is an Austronesian language of the Philippines primarily spoken in the Pampanga region of Central Luzon.
  • 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_69ca84730a5081908de282651019bf2f completed March 30, 2026, 2:10 p.m.
NER Named-entity recognition batch_69cd804c859081908c261ad16b501f0d completed April 1, 2026, 8:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69d12d0bf0c08190ab96db3eb522c91e completed April 4, 2026, 3:23 p.m.
Created at: March 30, 2026, 7:55 p.m.