Triple

T6612232
Position Surface form Disambiguated ID Type / Status
Subject Ennigerloh E149262 entity
Predicate locatedInRegion P40 FINISHED
Object Münsterland E177404 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: Münsterland | Statement: [Ennigerloh, locatedInRegion, Münsterland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Münsterland
Context triple: [Ennigerloh, locatedInRegion, Münsterland]
  • A. Münsterland chosen
    Münsterland is a rural region in northwestern Germany known for its historic castles, cycling routes, and traditional Westphalian culture.
  • B. Westfalen
    Westfalen is a historical region in northwestern Germany, now largely part of the state of North Rhine-Westphalia, known for its distinct cultural identity and medieval heritage.
  • C. South Westphalia
    South Westphalia is a region in western Germany known for its mixed industrial and rural character, encompassing parts of North Rhine-Westphalia including the Arnsberg area.
  • D. Emsland
    Emsland is a rural region in western Germany known for its agriculture, peatlands, and location along the River Ems near the Dutch border.
  • E. Giessenlanden
    Giessenlanden was a former municipality in the Dutch province of South Holland that later became part of the newly formed municipality of Molenlanden.
  • 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_69c687ebc680819094caf71faba2efe2 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6af3778a8819094e83afed7c6596f completed March 27, 2026, 4:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69c72f7450dc8190881a9347b8b9475f completed March 28, 2026, 1:31 a.m.
Created at: March 27, 2026, 1:57 p.m.