Triple

T13992148
Position Surface form Disambiguated ID Type / Status
Subject Mae E336606 entity
Predicate partOf P40 FINISHED
Object Namu Municipality E1073690 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: Namu Municipality | Statement: [Mae, partOf, Namu Municipality]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Namu Municipality
Context triple: [Mae, partOf, Namu Municipality]
  • A. Namu Municipality chosen
    Namu Municipality is a local administrative division that includes the settlement of Loen within its jurisdiction.
  • B. Mārupe Municipality
    Mārupe Municipality is an administrative region in Latvia, just outside Riga, known for hosting the country’s main international airport and serving as a growing suburban area of the capital.
  • C. Tabio Municipality
    Tabio Municipality is a small Andean town and municipality in the Cundinamarca Department of Colombia, known for its rural landscapes, cool climate, and proximity to Bogotá.
  • D. Tanum Municipality
    Tanum Municipality is a coastal municipality in western Sweden renowned for its extensive Bronze Age rock carvings, a UNESCO World Heritage Site.
  • E. Masku municipality
    Masku municipality is a small local government area in Southwest Finland known for its rural landscapes and proximity to the city of Turku.
  • 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_69de2eb3b5d881909f15a1e08bb202f3 completed April 14, 2026, 12:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69fbc32593e08190a1fe8466705c7fe8 completed May 6, 2026, 10:39 p.m.
Created at: April 9, 2026, 10:19 p.m.