Triple
T5123759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fränkische Rezat |
E115534
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Roth (district) |
E327828
|
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: Roth (district) | Statement: [Fränkische Rezat, flowsThrough, Roth (district)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roth (district) Context triple: [Fränkische Rezat, flowsThrough, Roth (district)]
-
A.
Roth (town)
Roth is a small town in Bavaria, Germany, known for its historic center and proximity to Nuremberg.
-
B.
district of Roth
chosen
The district of Roth is a rural administrative district in Middle Franconia, Bavaria, Germany, known for its mix of small towns, forests, and river landscapes.
-
C.
Roth bei Nürnberg (Austria)
Roth bei Nürnberg (Austria) is an Austrian town that is officially twinned with the German town of Roth in Bavaria.
-
D.
Ravensburg district
Ravensburg district is an administrative district (Landkreis) in the state of Baden-Württemberg in southern Germany, known for its historic towns, rural landscapes, and proximity to Lake Constance and the Alps.
-
E.
Wannsee district
Wannsee district is a lakeside area in southwestern Berlin known for its popular beaches, historic villas, and recreational waterfront attractions.
- 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_69bd4442ade0819087b9461f892b206b |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7805c55c8190bc0540d755dc6242 |
completed | March 20, 2026, 4:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bec4b7c628819097fb933be59ecefe |
completed | March 21, 2026, 4:17 p.m. |
Created at: March 20, 2026, 1:42 p.m.