Triple
T8259570
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Danube River at Donauwörth |
E193157
|
entity |
| Predicate | toponymContains |
P67829
|
FINISHED |
| Object | Donauwörth |
E368758
|
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: Donauwörth | Statement: [Danube River at Donauwörth, toponymContains, Donauwörth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Donauwörth Context triple: [Danube River at Donauwörth, toponymContains, Donauwörth]
-
A.
Donauwörth
chosen
Donauwörth is a historic Bavarian town in southern Germany situated at the confluence of the Danube and Lech rivers.
-
B.
Wolfratshausen
Wolfratshausen is a Bavarian town in southern Germany known for its historic old town, riverside setting on the Loisach and Isar, and proximity to Munich and the Alps.
-
C.
Zwiesel
Zwiesel is a prominent mountain in the Bavarian Alps of southeastern Germany, known for its scenic hiking routes and panoramic views over the Bad Reichenhall area.
-
D.
Straubing
Straubing is a Bavarian town on the Danube River known for its historic city center and role as a regional economic and educational hub.
-
E.
Erding
Erding is a Bavarian town northeast of Munich, best known for its historic center, Erdinger Weißbräu brewery, and large thermal spa complex.
- 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_69ca82dfad9c8190b8cd18fb89f50f40 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb793479d08190bd0dd8740bebff95 |
completed | March 31, 2026, 7:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfeace262881909dedeb1a07e95279 |
completed | April 3, 2026, 4:29 p.m. |
Created at: March 30, 2026, 5:49 p.m.