Triple
T3276124
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brigach |
E68761
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | St. Georgen im Schwarzwald |
E344274
|
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: St. Georgen im Schwarzwald | Statement: [Brigach, flowsThrough, St. Georgen im Schwarzwald]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: St. Georgen im Schwarzwald Context triple: [Brigach, flowsThrough, St. Georgen im Schwarzwald]
-
A.
St. Georgen im Schwarzwald
chosen
St. Georgen im Schwarzwald is a small town in Germany’s Black Forest region known for its high-altitude setting and surrounding forested landscapes.
-
B.
Georgensgmünd
Georgensgmünd is a market town in the Roth district of Bavaria, Germany, known for its location at the confluence of the Rednitz and Schwäbische Rezat rivers.
-
C.
Giengen an der Brenz
Giengen an der Brenz is a small town in the state of Baden-Württemberg in southern Germany, known as the birthplace of the Steiff teddy bear.
-
D.
Schwandorf
Schwandorf is a town in the Upper Palatinate region of Bavaria, Germany, known as a local administrative and commercial center on the Naab River.
-
E.
Grünau
Grünau is a waterside locality in Berlin known for its lakeside recreation areas, rowing facilities, and green residential surroundings.
- 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_69ad859b54f881909bf530d549caf2fd |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb0110f1c8190ae60708b686cbbf9 |
completed | March 8, 2026, 5:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2f3c764548190ac3c90da3763ac62 |
completed | March 12, 2026, 5:11 p.m. |
Created at: March 8, 2026, 3:10 p.m.