Triple

T15335566
Position Surface form Disambiguated ID Type / Status
Subject Bentheim E366654 entity
Predicate borderedBy P224 FINISHED
Object Steinfurt E692104 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: Steinfurt | Statement: [Bentheim, borderedBy, Steinfurt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Steinfurt
Context triple: [Bentheim, borderedBy, Steinfurt]
  • A. Steinfurt chosen
    Steinfurt is a historic town in western Germany’s North Rhine-Westphalia, known for its castle, old town, and location within the rural Münsterland region.
  • B. Rüdinghausen
    Rüdinghausen is a district of the city of Witten in North Rhine-Westphalia, Germany, characterized by its residential areas and local amenities.
  • C. Nordhorn
    Nordhorn is a town in Lower Saxony, Germany, known as the administrative center of the Grafschaft Bentheim district near the Dutch border.
  • D. Schlettstadt
    Schlettstadt, now known as Sélestat, is a historic town in the Alsace region of northeastern France noted for its medieval architecture and humanist heritage.
  • E. Radevormwald
    Radevormwald is a small historic town in North Rhine-Westphalia, western Germany, known for its hilly Bergisches Land landscape and traditional textile and metalworking industries.
  • 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_69d85a1355608190a6673ddb67231d54 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e03c5f081908e4d14dbdbc7f7a6 completed April 16, 2026, 1:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff9978ae90819088bf7c8890b7a9a5 completed May 9, 2026, 8:30 p.m.
Created at: April 10, 2026, 3:17 a.m.