Triple

T13980431
Position Surface form Disambiguated ID Type / Status
Subject Romblomanon E336293 entity
Predicate hasAlternativeName P39 FINISHED
Object Bisaya Romblon E706116 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: Bisaya Romblon | Statement: [Romblomanon, hasAlternativeName, Bisaya Romblon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bisaya Romblon
Context triple: [Romblomanon, hasAlternativeName, Bisaya Romblon]
  • A. Romblon Bisaya chosen
    Romblon Bisaya is an Austronesian language spoken in the Philippine province of Romblon, closely related to other Visayan languages.
  • B. Romblon
    Romblon is an island province in the Philippines known for its marble industry, clear waters, and scenic beaches.
  • C. Albay Bikol
    Albay Bikol is a Central Philippine language spoken in the Albay province of the Bicol Region in the Philippines, closely related to other Bikol languages.
  • D. Claveria
    Claveria is a coastal municipality in the Philippines known for its location along Macajalar Bay in Northern Mindanao.
  • E. Claveria
    Claveria is a coastal municipality in the Philippine province of Masbate known for its fishing communities and rural island landscapes.
  • 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_69d81c639e808190a0e4b4f3d31c6a59 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2ea10dc88190b9720919a021e570 completed April 14, 2026, 12:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcd0934b74819094ec7309c23a3e2a completed May 7, 2026, 5:49 p.m.
Created at: April 9, 2026, 10:18 p.m.