Triple

T18767372
Position Surface form Disambiguated ID Type / Status
Subject Ybanag E458925 entity
Predicate hasDialect P4251 FINISHED
Object Cagayan Ibanag NE NERFINISHED

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: Cagayan Ibanag | Statement: [Ybanag, hasDialect, Cagayan Ibanag]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cagayan Ibanag
Context triple: [Ybanag, hasDialect, Cagayan Ibanag]
  • A. Cagayanen
    Cagayanen is an Austronesian language spoken by the Cagayanen people of Cagayan de Sulu and nearby areas in the southern Philippines.
  • B. Cauayan
    Cauayan is a rapidly developing component city located in the province of Isabela in the Cagayan Valley region of the Philippines.
  • C. Ibanag chosen
    Ibanag is an Austronesian language spoken primarily in the Cagayan Valley region of northern Luzon in the Philippines.
  • D. Balingasag
    Balingasag is a coastal municipality in Misamis Oriental, Philippines, known for its fishing communities and access to Macajalar Bay.
  • E. Dipaculao
    Dipaculao is a coastal municipality in the Philippine province of Aurora known for its beaches, surfing spots, and scenic mountain landscapes.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d395dba0819087568404508590cb completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e58d859c8081909cec3aa64d264885 completed April 20, 2026, 2:20 a.m.
Created at: April 10, 2026, 11:52 a.m.