Triple

T9748414
Position Surface form Disambiguated ID Type / Status
Subject Cebu region E236374 entity
Predicate contains P35 FINISHED
Object Mandaue E261524 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: Mandaue | Statement: [Cebu region, contains, Mandaue]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mandaue
Context triple: [Cebu region, contains, Mandaue]
  • A. Mandaue City chosen
    Mandaue City is a highly urbanized and industrialized city in Metro Cebu in the central Philippines, known as a major commercial and manufacturing hub in the region.
  • B. Canlaon
    Canlaon is a city in the Philippines known for its proximity to Mount Kanlaon, an active volcano and prominent natural landmark on Negros Island.
  • C. Danao City
    Danao City is a component city in the province of Cebu in the Philippines, known historically for its gun-making industry and as a growing commercial and industrial hub in the region.
  • D. Danao
    Danao is a coastal city and municipality on Cebu Island in the Philippines known for its historical significance and local industries.
  • E. Cebu
    Cebu is a major island and province in the central Philippines known for its historic role in Spanish colonization, vibrant urban center Cebu City, and popular beach and dive tourism.
  • 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_69ca84d4eddc8190996fec1417d2bae8 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9f68f8b88190b44babf5ae17dfef completed April 1, 2026, 10:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1bcd2e08c8190808b58fdabe0c9d3 completed April 5, 2026, 1:37 a.m.
Created at: March 30, 2026, 8:23 p.m.