Triple

T7591520
Position Surface form Disambiguated ID Type / Status
Subject Little Belt E179745 entity
Predicate hasMajorPortNearby P5648 FINISHED
Object Fredericia E113948 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: Fredericia | Statement: [Little Belt, hasMajorPortNearby, Fredericia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fredericia
Context triple: [Little Belt, hasMajorPortNearby, Fredericia]
  • A. Fredericia chosen
    Fredericia is a Danish coastal town in Jutland known for its historic 17th-century fortress and well-preserved ramparts.
  • B. Frederikshavn
    Frederikshavn is a port town in northern Jutland, Denmark, known for its ferry connections to Norway and Sweden and its maritime industry.
  • C. Viborg
    Viborg is the Swedish name for the historic Karelian city of Vyborg, located near the Finnish border on the Gulf of Finland.
  • D. Vordingborg
    Vordingborg is a historic coastal town in southern Denmark known for the ruins of Vordingborg Castle and its prominent Goose Tower.
  • E. 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.
  • 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_69c69f335248819093c1006f30513708 completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c6f9b746ac8190b255afdfb9635f72 completed March 27, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69c963e3a3e0819092c6c7dd0dc82e7d completed March 29, 2026, 5:39 p.m.
Created at: March 27, 2026, 3:53 p.m.