Triple
T17429432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walhalla memorial |
E423828
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Donaustauf |
—
|
NE NERFINISHED |
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: Donaustauf | Statement: [Walhalla memorial, locatedIn, Donaustauf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Donaustauf Context triple: [Walhalla memorial, locatedIn, Donaustauf]
-
A.
Donaustauf
chosen
Donaustauf is a market town in Bavaria, Germany, situated on the Danube River just east of the city of Regensburg and known for the nearby Walhalla memorial.
-
B.
Linz
Linz is a major Austrian city known for its industrial heritage, vibrant cultural scene, and location along the Danube River.
-
C.
Tulln an der Donau
Tulln an der Donau is an Austrian town on the Danube River, known for its rich history and as the birthplace of painter Egon Schiele.
-
D.
Lenzburg
Lenzburg is a historic Swiss town in the canton of Aargau, known for its medieval hilltop castle and well-preserved old town.
-
E.
Gmunden
Gmunden is a picturesque town in Upper Austria known for its lakeside setting on the Traunsee and its historic ceramics industry.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889d88b6081908bada047f5b3ba51 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e448fe9e28819092a80f5686eb362f |
completed | April 19, 2026, 3:16 a.m. |
Created at: April 10, 2026, 5:46 a.m.