Triple
T16593799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pfinz |
E403155
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Pfinztal |
E821112
|
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: Pfinztal | Statement: [Pfinz, flowsThrough, Pfinztal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pfinztal Context triple: [Pfinz, flowsThrough, Pfinztal]
-
A.
Pfinztal
chosen
Pfinztal is a municipality in the Karlsruhe district of Baden-Württemberg, Germany, known for hosting research institutions such as the Fraunhofer Institute for Chemical Technology.
-
B.
Rauental
Rauental is a district of the German town of Rastatt in the state of Baden-Württemberg.
-
C.
Wiesloch
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.
-
D.
Tannheim
Tannheim is a small municipality in the district of Biberach in the German state of Baden-Württemberg, known for its rural character and Swabian cultural heritage.
-
E.
Eschbach
Eschbach is a village and district of the town of Usingen in the Hochtaunus region of Hesse, Germany.
- 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_69d883880d0c81908b5fcd454e767b60 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e35d6fcaa48190b1ba7dc3b792041a |
completed | April 18, 2026, 10:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00a508505881909cb7582916ad037c |
completed | May 10, 2026, 3:32 p.m. |
Created at: April 10, 2026, 5:16 a.m.