Triple

T1575417
Position Surface form Disambiguated ID Type / Status
Subject Funen E33638 entity
Predicate largestCity P235 FINISHED
Object Odense E164202 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: Odense | Statement: [Funen, largestCity, Odense]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Odense
Context triple: [Funen, largestCity, Odense]
  • A. Odense chosen
    Odense is a historic Danish city on the island of Funen, best known as the birthplace of fairy-tale author Hans Christian Andersen and a cultural hub with museums, festivals, and a vibrant literary heritage.
  • B. Kolding
    Kolding is a historic Danish city in Southern Jutland known for Koldinghus Castle, its fjord-side location, and its role as a regional cultural and educational center.
  • C. Esbjerg
    Esbjerg is a major Danish port city on the North Sea, known for its offshore oil and wind industry, maritime heritage, and role as a regional economic center in western Jutland.
  • D. Aarhus
    Aarhus is Denmark’s second-largest city, a major cultural and economic center on the Jutland peninsula known for its universities, vibrant arts scene, and historic harbor.
  • E. Randers
    Randers is a historic market town and one of the largest cities in eastern Jutland, Denmark, known for its old town center and location along the Gudenå River.
  • 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_69a885f27a4c8190a4622252cdf54c00 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a908d2cffc819090f3d5cbebae3307 completed March 5, 2026, 4:38 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae0aaae76c81909707184b3a3d87d5 completed March 8, 2026, 11:47 p.m.
Created at: March 4, 2026, 7:27 p.m.