Triple

T3770876
Position Surface form Disambiguated ID Type / Status
Subject Pampanga E83192 entity
Predicate hasDemonym P191 FINISHED
Object Kapampangan E82018 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: Kapampangan | Statement: [Pampanga, hasDemonym, Kapampangan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kapampangan
Context triple: [Pampanga, hasDemonym, Kapampangan]
  • A. Kapampangan chosen
    Kapampangan is an Austronesian language spoken primarily in the Pampanga region of the Philippines by the Kapampangan ethnic group.
  • B. Ibanag
    Ibanag is an Austronesian language spoken primarily in the Cagayan Valley region of northern Luzon in the Philippines.
  • C. Boholano
    Boholano is a regional variety of the Cebuano (Binisaya) language spoken primarily on the island of Bohol in the Philippines.
  • D. Albay Bikol
    Albay Bikol is a Central Philippine language spoken in the Albay province of the Bicol Region in the Philippines, closely related to other Bikol languages.
  • E. Yakan
    Yakan is an Austronesian language spoken primarily by the Yakan people of Basilan and nearby areas in the southern 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_69ad8b235e608190b5a2b1d1bfcef50b completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcc307cf8819090730b5e697bb197 completed March 8, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69b51c6dbd308190a2106a0711e226be completed March 14, 2026, 8:29 a.m.
Created at: March 8, 2026, 3:36 p.m.