Triple
T5247183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Limmat River |
E118490
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Wettingen |
E349667
|
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: Wettingen | Statement: [Limmat River, flowsThrough, Wettingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wettingen Context triple: [Limmat River, flowsThrough, Wettingen]
-
A.
Wettingen
chosen
Wettingen is a Swiss town in the canton of Aargau, located in the Limmat Valley near the city of Baden.
-
B.
Feuchtwangen
Feuchtwangen is a historic town in Bavaria, Germany, known for its medieval architecture and location along the Romantic Road.
-
C.
Weiningen
Weiningen is a small Swiss municipality in the canton of Zurich, located in the Limmat Valley near the city of Zurich.
-
D.
Schwenningen
Schwenningen is a district of Villingen-Schwenningen in Baden-Württemberg, Germany, known for its ice hockey tradition and as the home of the Schwenninger Wild Wings.
-
E.
Wüllen
Wüllen is a district of the town of Ahaus in North Rhine-Westphalia, Germany, known for its rural character within the Münsterland region.
- 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_69bd4468aacc8190a8196f71855cdf4f |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7b5320748190bcf3be4b6c364f92 |
completed | March 20, 2026, 4:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bef836d158819092cdd22e0dbc9dae |
completed | March 21, 2026, 7:57 p.m. |
Created at: March 20, 2026, 1:50 p.m.