Triple
T16711031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beverley |
E406105
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Lemgo |
E357782
|
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: Lemgo | Statement: [Beverley, hasTwinTown, Lemgo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lemgo Context triple: [Beverley, hasTwinTown, Lemgo]
-
A.
Lemgo
chosen
Lemgo is a historic town in the Lippe district of North Rhine-Westphalia, Germany, known for its well-preserved medieval architecture and Hanseatic heritage.
-
B.
Meppen
Meppen is a historic town in Lower Saxony, Germany, known as a regional center in the Emsland district near the Dutch border.
-
C.
Lüdinghausen
Lüdinghausen is a historic town in western Germany known for its medieval castles and picturesque setting in the Münsterland region.
-
D.
Gummersbach
Gummersbach is a town in North Rhine-Westphalia, Germany, known as a regional center in the Bergisches Land and a location for higher education and industry.
-
E.
Lohmar
Lohmar is a town in the Rhein-Sieg district of North Rhine-Westphalia, Germany, situated near Cologne and known for its green surroundings and residential character.
- 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_69d8838db21081909589220fd71440a4 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e386523fc08190a13a4232af191992 |
completed | April 18, 2026, 1:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00dbf92b148190825778809bc4aac2 |
completed | May 10, 2026, 7:26 p.m. |
Created at: April 10, 2026, 5:20 a.m.