Triple

T8046366
Position Surface form Disambiguated ID Type / Status
Subject Molde FK E187563 entity
Predicate homeCity P263 FINISHED
Object Molde E75759 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: Molde | Statement: [Molde FK, homeCity, Molde]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Molde
Context triple: [Molde FK, homeCity, Molde]
  • A. Molde chosen
    Molde is a coastal town in western Norway known for its scenic fjord views, mild climate, and annual international jazz festival.
  • B. Elverum
    Elverum is a town and municipality in Innlandet county in eastern Norway, known for its forestry, military camp, and role in Norwegian World War II history.
  • C. Sarpsborg
    Sarpsborg is a historic city and municipality in Viken county, Norway, known as one of the country’s oldest towns and an important industrial and administrative center in the Østfold region.
  • D. Hønefoss
    Hønefoss is a Norwegian town known as a regional commercial and transport hub, situated along the Begna River northwest of Oslo.
  • E. Porsgrunn
    Porsgrunn is an industrial and port city in Telemark county in southeastern Norway, known for its porcelain production and location along the Telemark Canal.
  • 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_69ca82b00cb48190b59a300f70e97bd7 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3f4d9ddc8190a7dcf85ed47ee6c3 completed March 31, 2026, 3:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc63d03c9481909ccddd9580216506 completed April 1, 2026, 12:16 a.m.
Created at: March 30, 2026, 5:24 p.m.