Triple

T19269787
Position Surface form Disambiguated ID Type / Status
Subject Province of Capiz E481890 entity
Predicate hasMunicipality P847 FINISHED
Object Sapian 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: Sapian | Statement: [Province of Capiz, hasMunicipality, Sapian]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sapian
Context triple: [Province of Capiz, hasMunicipality, Sapian]
  • A. Sapian chosen
    Sapian is a coastal municipality in the province of Capiz in the Philippines, known for its fishing industry and scenic bay.
  • B. Sapieha
    Sapieha is the name of a prominent Polish–Lithuanian magnate family that played a significant political and military role in the Polish–Lithuanian Commonwealth.
  • C. Sapru
    Sapru is an Indian surname historically associated with a prominent Kashmiri Pandit family known for producing notable lawyers, politicians, and public figures.
  • D. Sabaot
    Sabaot is a Southern Nilotic language spoken primarily by the Sabaot people in the Mount Elgon region of Kenya and Uganda.
  • E. Saka
    Saka is an ancient Eastern Iranian language once spoken by the Saka people in the Tarim Basin region of Central Asia.
  • 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_69d8e8ce54cc8190998418ff1f66ef28 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5fbb74ec48190a58d96b4b5b9af00 completed April 20, 2026, 10:11 a.m.
Created at: April 10, 2026, 1:29 p.m.