Triple
T20849508
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | B 3 |
E513317
|
entity |
| Predicate | connects |
P390
|
FINISHED |
| Object | Wiesloch |
—
|
NE NERFINISHED |
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: Wiesloch | Statement: [B 3, connects, Wiesloch]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wiesloch Context triple: [B 3, connects, Wiesloch]
-
A.
Wiesloch
chosen
Wiesloch is a town in the Rhine-Neckar district of Baden-Württemberg, Germany, known for its historical center and role as a regional commercial hub.
-
B.
Ettlingen
Ettlingen is a historic town in the state of Baden-Württemberg in southwestern Germany, known for its well-preserved old town and proximity to the city of Karlsruhe.
-
C.
Waldbronn
Waldbronn is a municipality in the state of Baden-Württemberg in southwestern Germany, known for its spa facilities and proximity to the city of Karlsruhe.
-
D.
Tuttlingen
Tuttlingen is a town in the state of Baden-Württemberg in southern Germany, known as a major center of the medical technology and surgical instrument industry.
-
E.
Blaubeuren
Blaubeuren is a historic town in the Alb-Donau district of Baden-Württemberg, Germany, known for its medieval old town and the karst spring Blautopf.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4f4898081908209e58edb8f9c45 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c3520b0081908ce0f43e8f20b24c |
completed | April 21, 2026, 12:22 a.m. |
Created at: April 16, 2026, 12:43 p.m.