Triple
T15968881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hiddenhausen |
E387267
|
entity |
| Predicate | hasNeighbouringMunicipality |
P224
|
FINISHED |
| Object | Löhne |
E387268
|
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: Löhne | Statement: [Hiddenhausen, hasNeighbouringMunicipality, Löhne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Löhne Context triple: [Hiddenhausen, hasNeighbouringMunicipality, Löhne]
-
A.
Löhne
chosen
Löhne is a town in the district of Herford in North Rhine-Westphalia, Germany, known historically as part of the former County of Ravensberg.
-
B.
Südlohn
Südlohn is a municipality in western North Rhine-Westphalia, Germany, near the Dutch border.
-
C.
Hohberg
Hohberg is a municipality in the Ortenau district of Baden-Württemberg in southwestern Germany.
-
D.
Brannenburg
Brannenburg is a Bavarian municipality in southern Germany, known for its scenic Alpine setting and outdoor recreation opportunities.
-
E.
Reisenberg
Reisenberg is a small municipality in Lower Austria’s Baden District, known for its rural character and proximity to Vienna.
- 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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1572847f08190830e30125e829766 |
completed | April 16, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffbe88fa308190942d37cf67458396 |
completed | May 9, 2026, 11:08 p.m. |
Created at: April 10, 2026, 4:54 a.m.