Triple

T7997844
Position Surface form Disambiguated ID Type / Status
Subject Foley E186171 entity
Predicate associatedWithRegion P285 FINISHED
Object Munster E61441 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: Munster | Statement: [Foley, associatedWithRegion, Munster]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Munster
Context triple: [Foley, associatedWithRegion, 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. Leinster
    Leinster is a province in eastern Ireland that includes the capital city, Dublin, and is the country’s most populous region.
  • E. Connacht
    Connacht is one of the four traditional provinces of Ireland, located in the west of the island and historically known for its Gaelic culture and rugged landscapes.
  • 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_69ca829c6c308190ab05b43d234c52b2 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3c98e39081908904d36a31bd6768 completed March 31, 2026, 3:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69cbe10d5eb081909f257390094de442 completed March 31, 2026, 2:58 p.m.
Created at: March 30, 2026, 5:17 p.m.