Triple

T14311395
Position Surface form Disambiguated ID Type / Status
Subject Enschede E354840 entity
Predicate isTwinnedWith P102611 FINISHED
Object Münster E40803 NE FINISHED

How this triple was built (3 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: Münster | Statement: [Enschede, isTwinnedWith, Münster]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Münster
Context triple: [Enschede, isTwinnedWith, Münster]
  • A. Münster chosen
    Münster is a historic city in western Germany known as one of the principal sites where the Peace of Westphalia treaties were negotiated and signed, ending the Thirty Years' War in 1648.
  • B. Osnabrück
    Osnabrück is a historic city in Lower Saxony, Germany, known for its medieval architecture and role in the Peace of Westphalia.
  • C. Paderborn
    Paderborn is a historic city in western Germany known for its medieval cathedral, role as a regional religious and cultural center, and strategic importance during World War II.
  • D. Lippstadt
    Lippstadt is a historic town in North Rhine-Westphalia, Germany, known for its medieval architecture and role in regional conflicts.
  • E. Cologne
    Cologne is a historic German city on the Rhine River, renowned for its Gothic cathedral, vibrant cultural scene, and status as a major economic and media hub.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: isTwinnedWith
Context triple: [Enschede, isTwinnedWith, Münster]
  • A. isTwinWith
    Indicates that two entities are twins, sharing the same birth parents and being born at (or very near) the same time.
  • B. hasTwin
    Indicates that one entity is a twin of another, sharing the same birth event or time with a sibling.
  • C. twinning chosen
    Indicates that two entities are paired or linked as twins, typically sharing a formally recognized, parallel, or closely matched relationship.
  • D. hasTwinStructureWith
    Indicates that two entities share an identical or nearly identical structural form, typically as corresponding or mirrored counterparts.
  • E. hasTwinCharacters
    Indicates that two characters are twins, sharing the same parents and birth time or very close birth times.
  • F. None of above.

Provenance (4 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_69d8278ed42c8190b9f882dcce611347 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de85b386d0819087d14f3ce84a1997 completed April 14, 2026, 6:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff2189c1cc819080dc296b17e42374 completed May 9, 2026, 11:59 a.m.
PD Predicate disambiguation batch_69de2a8f81f08190af737e1654847aa6 completed April 14, 2026, 11:52 a.m.
Created at: April 10, 2026, 1:12 a.m.