Triple

T7462739
Position Surface form Disambiguated ID Type / Status
Subject Tierp Municipality E176291 entity
Predicate administrativeCenter P1474 FINISHED
Object Tierp E146819 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: Tierp | Statement: [Tierp Municipality, administrativeCenter, Tierp]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tierp
Context triple: [Tierp Municipality, administrativeCenter, Tierp]
  • A. Tierp chosen
    Tierp is a locality and municipal seat in east-central Sweden known for its rural surroundings and motorsport activities, including the Tierp Arena drag racing track.
  • B. Tierney
    Tierney is an Irish-origin surname borne by various notable individuals in fields such as sports, politics, and the arts.
  • C. Tipner
    Tipner is a residential and industrial suburb in the northwest of Portsmouth, England, known for its waterfront location and proximity to major transport routes.
  • D. Tupe
    Tupe is a small Andean town in Peru known for preserving the unique Jaqaru indigenous language and culture.
  • E. Tepiman
    Tepiman is a subgroup of Uto-Aztecan languages spoken primarily in the southwestern United States and northern Mexico, including languages such as O'odham and Tepehuán.
  • 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_69c69f21632481908bf83f6c6da897e3 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f3d80ae08190ba383066cf0cb2ce completed March 27, 2026, 9:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c83c5f1f408190a7d42abe28605ddb completed March 28, 2026, 8:38 p.m.
Created at: March 27, 2026, 3:39 p.m.