Triple

T7592329
Position Surface form Disambiguated ID Type / Status
Subject Western Malayo-Polynesian (traditional classification) E179765 entity
Predicate includesLanguage P2177 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: [Western Malayo-Polynesian (traditional classification), includesLanguage, Kapampangan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kapampangan
Context triple: [Western Malayo-Polynesian (traditional classification), includesLanguage, 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. Sugbuanon
    Sugbuanon refers to the Cebuano people, a Visayan ethnolinguistic group from the central and southern Philippines known for speaking the Cebuano language.
  • D. Boholano
    Boholano is a regional variety of the Cebuano (Binisaya) language spoken primarily on the island of Bohol in the Philippines.
  • E. Pangasinense
    Pangasinense is an Austronesian language spoken primarily in the province of Pangasinan 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_69c69f335248819093c1006f30513708 completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c6f9b92c348190b547f0aacfb8d6be completed March 27, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69c86197fe0881908307a411cabdca7f completed March 28, 2026, 11:17 p.m.
Created at: March 27, 2026, 3:53 p.m.