Triple

T15917650
Position Surface form Disambiguated ID Type / Status
Subject Palanan, Isabela, Philippines E386009 entity
Predicate locatedIn P40 FINISHED
Object Isabela E308468 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: Isabela | Statement: [Palanan, Isabela, Philippines, locatedIn, Isabela]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Isabela
Context triple: [Palanan, Isabela, Philippines, locatedIn, Isabela]
  • A. Isabela chosen
    Isabela is a large agricultural province in the Cagayan Valley region of the Philippines, known especially for its extensive rice and corn production.
  • B. Isabela
    Isabela is a coastal municipality in northwestern Puerto Rico known for its beaches, surfing spots, and scenic Atlantic shoreline.
  • C. Rosana
    Rosana is a municipality in the state of São Paulo, Brazil, known for hosting a campus of São Paulo State University (UNESP).
  • D. Rosana
    Rosana is a Brazilian professional footballer known for her successful international career and contributions to top women’s clubs, including Avaldsnes IL.
  • E. Cayetana
    Cayetana is the given name of Cayetana Fitz-James Stuart, the 18th Duchess of Alba, a prominent Spanish aristocrat known for holding a record number of noble titles.
  • 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_69d86da686e4819097cbf3b1fc2d881d completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1567ef7f881908862eaf5bf2e98fd completed April 16, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffb5a79b808190850fa9d327f7ef72 completed May 9, 2026, 10:31 p.m.
Created at: April 10, 2026, 4:52 a.m.