Triple
T15875767
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kocher |
E384948
|
entity |
| Predicate | nearbyCity |
P350
|
FINISHED |
| Object |
Ellwangen (Jagst)
Ellwangen (Jagst) is a historic town in the German state of Baden-Württemberg, known for its well-preserved old town, baroque basilica, and former prince-provost residence.
|
E1181007
|
NE FINISHED |
How this triple was built (4 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: Ellwangen (Jagst) | Statement: [Kocher, nearbyCity, Ellwangen (Jagst)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ellwangen (Jagst) Context triple: [Kocher, nearbyCity, Ellwangen (Jagst)]
-
A.
Feuchtwangen
Feuchtwangen is a historic town in Bavaria, Germany, known for its medieval architecture and location along the Romantic Road.
-
B.
Wuhletal
Wuhletal is a valley landscape in Berlin shaped by the course of the Wuhle river, featuring green spaces, walking paths, and recreational areas.
-
C.
Wüllen
Wüllen is a district of the town of Ahaus in North Rhine-Westphalia, Germany, known for its rural character within the Münsterland region.
-
D.
Eifgenbach
Eifgenbach is a small river in North Rhine-Westphalia, Germany, that flows through the Bergisches Land region before joining the Wupper.
-
E.
Eschbach
Eschbach is a village and district of the town of Usingen in the Hochtaunus region of Hesse, Germany.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ellwangen (Jagst) Triple: [Kocher, nearbyCity, Ellwangen (Jagst)]
Generated description
Ellwangen (Jagst) is a historic town in the German state of Baden-Württemberg, known for its well-preserved old town, baroque basilica, and former prince-provost residence.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ellwangen (Jagst) Target entity description: Ellwangen (Jagst) is a historic town in the German state of Baden-Württemberg, known for its well-preserved old town, baroque basilica, and former prince-provost residence.
-
A.
Feuchtwangen
Feuchtwangen is a historic town in Bavaria, Germany, known for its medieval architecture and location along the Romantic Road.
-
B.
Wuhletal
Wuhletal is a valley landscape in Berlin shaped by the course of the Wuhle river, featuring green spaces, walking paths, and recreational areas.
-
C.
Wüllen
Wüllen is a district of the town of Ahaus in North Rhine-Westphalia, Germany, known for its rural character within the Münsterland region.
-
D.
Eifgenbach
Eifgenbach is a small river in North Rhine-Westphalia, Germany, that flows through the Bergisches Land region before joining the Wupper.
-
E.
Eschbach
Eschbach is a village and district of the town of Usingen in the Hochtaunus region of Hesse, Germany.
- F. None of above. chosen
Provenance (5 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_69d86da4e86481909f1325fdc971b5ec |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e155fcffbc8190ba6d133107b83a7f |
completed | April 16, 2026, 9:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffa94e9b548190bec74e6d9790d241 |
completed | May 9, 2026, 9:38 p.m. |
| NEDg | Description generation | batch_69ffaa07df788190bae67f3d9a800331 |
completed | May 9, 2026, 9:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffaaa92a648190a09829ef3197223c |
completed | May 9, 2026, 9:44 p.m. |
Created at: April 10, 2026, 4:51 a.m.