Triple

T892718
Position Surface form Disambiguated ID Type / Status
Subject Raisa Gorbacheva E19275 entity
Predicate placeOfDeath P21 FINISHED
Object Münster E40803 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: Münster | Statement: [Raisa Gorbacheva, placeOfDeath, Münster]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Münster
Context triple: [Raisa Gorbacheva, placeOfDeath, 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. 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.
  • D. Detmold
    Detmold is a historic town in northwestern Germany that served as the capital and residence city of the former Principality of Lippe.
  • E. Düsseldorf
    Düsseldorf is a major German city on the Rhine River known for its fashion and art scenes, modern architecture, and status as an important economic and financial 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_69a4939d37188190848be3d426ebc9ae completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ad0304b081908d4c92bb2beadb81 completed March 1, 2026, 9:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69af2b3a21248190aca7710ae6ad6478 completed March 9, 2026, 8:19 p.m.
Created at: March 1, 2026, 7:39 p.m.