Triple
T12566938
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Westphalia |
E295497
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Dörentrup |
E786766
|
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: Dörentrup | Statement: [Province of Westphalia, containsSettlement, Dörentrup]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dörentrup Context triple: [Province of Westphalia, containsSettlement, Dörentrup]
-
A.
Dörentrup
chosen
Dörentrup is a small municipality in the Lippe district of North Rhine-Westphalia, Germany, known for its rural character and location within the Teutoburg Forest region.
-
B.
Donsbach
Donsbach is a village and district of the town of Dillenburg in the Lahn-Dill-Kreis region of Hesse, Germany.
-
C.
Dierdorf
Dierdorf is a surname most prominently associated with former American football player and sportscaster Dan Dierdorf.
-
D.
Nordendorf
Nordendorf is a small municipality in Bavaria, Germany, situated within the Augsburg district.
-
E.
Adendorf
Adendorf is a village-sized district within the municipality of Wachtberg in the Rhein-Sieg-Kreis region of North Rhine-Westphalia, Germany.
- 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_69d6ad9cac2c81908e8a7bed82d1e21d |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d954a325948190994bcfc9d571a3a8 |
completed | April 10, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6a537bb1881908a50073d4f27b66c |
completed | May 3, 2026, 1:30 a.m. |
Created at: April 8, 2026, 11:49 p.m.