Triple
T10078319
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wessum |
E213830
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Ahaus |
E28702
|
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: Ahaus | Statement: [Wessum, partOf, Ahaus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ahaus Context triple: [Wessum, partOf, Ahaus]
-
A.
Ahaus
chosen
Ahaus is a town in the district of Borken in North Rhine-Westphalia, western Germany, known for its historic castle and role as a regional administrative and cultural center.
-
B.
Boppard
Boppard is a historic town on the Rhine River in Germany, renowned for its well-preserved medieval architecture, wine culture, and scenic river landscapes.
-
C.
Montabaur
Montabaur is a historic town in western Germany’s Rhineland-Palatinate region, known for its distinctive hilltop castle and well-preserved old town.
-
D.
Benrath
Benrath is a German surname most notably associated with the late actor Martin Benrath.
-
E.
Xanten
Xanten is a historic town in western Germany known for its well-preserved Roman archaeological park and medieval architecture.
- 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_69ca839bf730819086900c323c9b8c95 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd030a0fc819084b523e8e63636fa |
completed | April 2, 2026, 2:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2cbc0388c8190bc10d462068c9e38 |
completed | April 5, 2026, 8:53 p.m. |
Created at: March 30, 2026, 9 p.m.