Triple

T22342177
Position Surface form Disambiguated ID Type / Status
Subject College of Business and Law E552301 entity
Predicate locatedIn P40 FINISHED
Object Munster NE NERFINISHED

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: Munster | Statement: [College of Business and Law, locatedIn, Munster]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Munster
Context triple: [College of Business and Law, locatedIn, Munster]
  • A. Munster
    Munster is a small town in the Grand Est region of northeastern France, known for its namesake strong-smelling cheese and picturesque setting in the Vosges mountains.
  • B. Munster chosen
    Munster is a historic province in the south of Ireland, known for its major role in Irish history, culture, and conflicts, including the 17th-century wars.
  • C. Munster
    Munster is a town in Lower Saxony, Germany, known for its military training areas and location within the Lüneburg Heath region.
  • D. Munster
    Munster is the fictional family surname of the quirky monster household featured in the classic American television sitcom "The Munsters."
  • E. Leinster
    Leinster is a province in eastern Ireland that includes the capital city, Dublin, and is the country’s most populous region.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e494eec81909c4d2d51f69499d9 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15794fae48190a2b79e9ae4b57bb1 completed April 29, 2026, 12:57 a.m.
Created at: April 16, 2026, 8:43 p.m.