Triple

T15984142
Position Surface form Disambiguated ID Type / Status
Subject Sittaung River basin E387647 entity
Predicate hasMajorCityInBasin P33130 FINISHED
Object Bago E779655 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: Bago | Statement: [Sittaung River basin, hasMajorCityInBasin, Bago]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bago
Context triple: [Sittaung River basin, hasMajorCityInBasin, Bago]
  • A. Bago
    Bago is a component city in the province of Negros Occidental in the Philippines, known for its agricultural economy and historical significance.
  • B. Bago chosen
    Bago is a historic city in southern Myanmar known for its ancient Buddhist monuments and proximity to Yangon.
  • C. Bago
    Bago is an indigenous ethnolinguistic group in the northern Philippines, primarily associated with the Ilocos and Cordillera regions.
  • D. Bagà
    Bagà is a historic town in Catalonia, Spain, known for its medieval old quarter and location in the Pyrenees.
  • E. Bacuag
    Bacuag is a coastal municipality in the province of Surigao del Norte in the Philippines, known for its fishing communities and access to rich marine resources.
  • 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_69d86daa562c81908aacc179c0fe8fb5 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e15756d6488190ac35da00e96ce21d completed April 16, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffc3cdf7848190848e9081027dc027 completed May 9, 2026, 11:31 p.m.
Created at: April 10, 2026, 4:54 a.m.