Triple

T3754769
Position Surface form Disambiguated ID Type / Status
Subject Kapampangan E82018 entity
Predicate hasAlternativeName P39 FINISHED
Object Capampañgan 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: Capampañgan | Statement: [Kapampangan, hasAlternativeName, Capampañgan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Capampañgan
Context triple: [Kapampangan, hasAlternativeName, Capampañgan]
  • 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. Malpaso
    Malpaso is the highest peak on the Canary Island of El Hierro, known for its panoramic views over the island and surrounding Atlantic Ocean.
  • D. Canlaon
    Canlaon is a city in the Philippines known for its proximity to Mount Kanlaon, an active volcano and prominent natural landmark on Negros Island.
  • E. Dalaguete
    Dalaguete is a coastal municipality in the province of Cebu in the Philippines, known for its cool highland areas and vegetable farming.
  • 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_69ad8b1db40081908b61ffa6b78afd4d completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcb94ffc08190a7fd1ce71a15f787 completed March 8, 2026, 7:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4e50825588190b620950ac1d4f408 completed March 14, 2026, 4:33 a.m.
Created at: March 8, 2026, 3:35 p.m.