Triple

T19031704
Position Surface form Disambiguated ID Type / Status
Subject La Union E465754 entity
Predicate hasMunicipality P847 FINISHED
Object Tubao 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: Tubao | Statement: [La Union, hasMunicipality, Tubao]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tubao
Context triple: [La Union, hasMunicipality, Tubao]
  • A. Tubao chosen
    Tubao is a municipality in the province of La Union in the Ilocos Region of the Philippines, known for its predominantly agricultural economy and rural communities.
  • B. Houtong
    Houtong is a small village in New Taipei, Taiwan, best known for its former coal-mining industry and its popular cat-themed tourism.
  • C. Sihui
    Sihui is a major Beijing Subway station in eastern Beijing that serves as a key interchange and endpoint for multiple metro lines.
  • D. Maoping
    Maoping is a historic village in China’s Jinggangshan region known as an early revolutionary stronghold and base area of the Chinese Red Army and Communist leadership.
  • E. Raoping
    Raoping is a coastal county in eastern Guangdong, China, known for its Teochew culture and strategic location along major transport routes.
  • 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_69d8dd0359648190bc2a9202c5cf29d2 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d7410dd08190b08a7c0a2b8d67f3 completed April 20, 2026, 7:35 a.m.
Created at: April 10, 2026, 12:02 p.m.