Triple

T16236488
Position Surface form Disambiguated ID Type / Status
Subject Capampangan E394125 entity
Predicate hasAlternativeName P39 FINISHED
Object Pampangan E385601 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: Pampangan | Statement: [Capampangan, hasAlternativeName, Pampangan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pampangan
Context triple: [Capampangan, hasAlternativeName, Pampangan]
  • A. Pampangan chosen
    Pampangan is an alternative name for Kapampangan, an Austronesian language and ethnolinguistic group native to the Pampanga region in the Philippines.
  • B. Pantanaw
    Pantanaw is a town in Myanmar’s Ayeyarwady Region, historically noted as the birthplace of former UN Secretary-General U Thant.
  • C. Paguay
    Paguay is the former historic name of the city now known as Poway in San Diego County, California.
  • D. Kaurareg
    Kaurareg is a dialect of the Kalaw Lagaw Ya language traditionally spoken by the Kaurareg people of the Torres Strait in northern Australia.
  • E. Tarempa
    Tarempa is the main town and hub of government, commerce, and transportation in Indonesia’s Anambas Islands.
  • 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_69d87f204df88190a8f88923decf9835 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2455abc608190ba3308c15c9e8a23 completed April 17, 2026, 2:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a000ed8cbe48190be68ccade55211ad completed May 10, 2026, 4:51 a.m.
Created at: April 10, 2026, 5:04 a.m.