Triple
T14856955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bad Laasphe |
E349382
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Siegen-Wittgenstein |
E413003
|
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: Siegen-Wittgenstein | Statement: [Bad Laasphe, partOf, Siegen-Wittgenstein]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Siegen-Wittgenstein Context triple: [Bad Laasphe, partOf, Siegen-Wittgenstein]
-
A.
Siegen-Wittgenstein
chosen
Siegen-Wittgenstein is a rural district in the German state of North Rhine-Westphalia, known for its forested low mountain landscapes and the city of Siegen as its administrative center.
-
B.
Siegen
Siegen is a city in western Germany known as the birthplace of the Baroque painter Peter Paul Rubens and for its historic mining and university traditions.
-
C.
Solingen
Solingen is a city in western Germany renowned for its centuries-old blade-making tradition and production of high-quality knives and swords.
-
D.
Wehrheim
Wehrheim is a small municipality in the Hochtaunus district of Hesse, Germany, known for its rural character and proximity to the Taunus mountain range.
-
E.
Kaiserslautern
Kaiserslautern is a city in southwestern Germany known for its historic old town, technical university, and prominent football club 1. FC Kaiserslautern.
- 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_69d822ed7e1881909b90fca143ad7e34 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded44458ec8190be295a95f5daab14 |
completed | April 14, 2026, 11:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff4c2a938081909ccd9fe7c5021dc6 |
completed | May 9, 2026, 3 p.m. |
Created at: April 10, 2026, 1:54 a.m.