Triple

T20025520
Position Surface form Disambiguated ID Type / Status
Subject Province of Leyte E494972 entity
Predicate hasMunicipality P847 FINISHED
Object Burauen 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: Burauen | Statement: [Province of Leyte, hasMunicipality, Burauen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Burauen
Context triple: [Province of Leyte, hasMunicipality, Burauen]
  • A. Burauen chosen
    Burauen is a municipality in the province of Leyte in the Philippines, known for its rural landscapes and natural attractions such as springs and waterfalls.
  • B. Baunei
    Baunei is a coastal and mountain village in Sardinia, Italy, known for its dramatic limestone cliffs, hiking trails, and the famous Cala Goloritzé beach.
  • C. Panabo
    Panabo is a coastal component city in Davao del Norte, Philippines, known for its extensive banana plantations and role in the region’s agricultural economy.
  • D. Hahaya
    Hahaya is a village on Grande Comore in the Comoros best known for hosting the country’s main international airport.
  • E. Salaga
    Salaga is a historic town in northern Ghana that once served as a major hub in the trans-Saharan slave trade.
  • 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_69da626bfd288190aa5d65098b6433ae completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6628d5b8c8190a35f95ac4a016550 completed April 20, 2026, 5:29 p.m.
Created at: April 11, 2026, 3:35 p.m.