Triple

T17008535
Position Surface form Disambiguated ID Type / Status
Subject Kirsten Munk E412636 entity
Predicate residence P75 FINISHED
Object Nyborg Castle E676679 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: Nyborg Castle | Statement: [Kirsten Munk, residence, Nyborg Castle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nyborg Castle
Context triple: [Kirsten Munk, residence, Nyborg Castle]
  • A. Nyborg Castle chosen
    Nyborg Castle is a historic medieval fortress and former royal residence located in the town of Nyborg on the Danish island of Funen.
  • B. Vordingborg Castle
    Vordingborg Castle is a historic medieval fortress in Denmark, closely associated with the royal power and military campaigns of King Valdemar II.
  • C. Sønderborg Castle
    Sønderborg Castle is a historic Danish fortress and former royal residence on the island of Als, notable for its role in Denmark’s royal and military history.
  • D. Søborg Castle
    Søborg Castle was a medieval stronghold in northern Zealand, Denmark, historically significant as a royal residence and fortress.
  • E. Kalundborg Castle
    Kalundborg Castle was a significant medieval royal stronghold in the Danish town of Kalundborg, historically used as a residence and fortress by Danish monarchs.
  • 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_69d886cb581c8190ab05f4b429c9cd85 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d3853f548190910240a2145cc890 completed April 18, 2026, 6:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00dc222d108190934ef2b3aa46aa22 completed May 10, 2026, 7:27 p.m.
Created at: April 10, 2026, 5:32 a.m.