Triple

T3855763
Position Surface form Disambiguated ID Type / Status
Subject Cebuano people E90010 entity
Predicate nativeName P15 FINISHED
Object Bisaya 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: Bisaya | Statement: [Cebuano people, nativeName, Bisaya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bisaya
Context triple: [Cebuano people, nativeName, Bisaya]
  • A. Binisaya chosen
    Binisaya is a major Austronesian language of the Philippines, widely spoken in the Central Visayas and parts of Mindanao.
  • B. Waray of Samar
    Waray of Samar is a major regional language variety spoken on the island of Samar in the Eastern Visayas region of the Philippines.
  • C. Waray language
    Waray is an Austronesian language spoken primarily in the Eastern Visayas region of the Philippines, particularly on Samar and nearby islands.
  • D. Butuanon language
    The Butuanon language is an Austronesian language spoken primarily in and around Butuan City in Mindanao, Philippines.
  • E. Winaray
    Winaray is an Austronesian language spoken primarily in the Eastern Visayas region of the Philippines, particularly in Samar, northern Leyte, and nearby areas.
  • 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_69aed95b3c088190a8f85d19e6070599 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeec07d45081909b8f3e35eb710f4c completed March 9, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5041f40f88190883339db0950026a completed March 14, 2026, 6:45 a.m.
Created at: March 9, 2026, 3:19 p.m.