Triple

T16812142
Position Surface form Disambiguated ID Type / Status
Subject Gjøvik municipal council E408640 entity
Predicate meetsIn P40 FINISHED
Object Gjøvik city hall E408639 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: Gjøvik city hall | Statement: [Gjøvik municipal council, meetsIn, Gjøvik city hall]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gjøvik city hall
Context triple: [Gjøvik municipal council, meetsIn, Gjøvik city hall]
  • A. Gjøvik Town Hall chosen
    Gjøvik Town Hall is the main municipal administrative building and civic center of the town of Gjøvik in Norway.
  • B. Haugesund city hall
    Haugesund city hall is the main administrative and political center of the city of Haugesund in Norway, housing its municipal government offices and council chambers.
  • C. Kristiansund city hall
    Kristiansund city hall is the main administrative and political center of the Norwegian city of Kristiansund, housing its municipal government and public offices.
  • D. Stavanger city hall
    Stavanger city hall is the main municipal government building of Stavanger, Norway, housing the city’s administrative offices and political leadership.
  • E. Lillehammer city hall
    Lillehammer city hall is the main administrative and political center of the city of Lillehammer, Norway, housing its municipal government offices and council chambers.
  • 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_69d88393905081908d00a86b99996ac8 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3b2df5c888190a462614e1432c357 completed April 18, 2026, 4:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00b292a5888190812539b14eb77f34 completed May 10, 2026, 4:30 p.m.
Created at: April 10, 2026, 5:23 a.m.