Triple
T20886812
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mattsies |
E514302
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Tussenhausen |
—
|
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: Tussenhausen | Statement: [Mattsies, locatedNear, Tussenhausen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tussenhausen Context triple: [Mattsies, locatedNear, Tussenhausen]
-
A.
Tussenhausen
chosen
Tussenhausen is a municipality in the district of Unterallgäu in Bavaria, Germany, known for its rural character and small villages such as Mattsies.
-
B.
Hubersdorf
Hubersdorf is a small municipality located in the canton of Solothurn in northwestern Switzerland.
-
C.
Hettenshausen
Hettenshausen is a municipality in the district of Pfaffenhofen an der Ilm in Bavaria, Germany.
-
D.
Wolpertshausen
Wolpertshausen is a small rural municipality in the German state of Baden-Württemberg, known for its agricultural character and location within the Hohenlohe region.
-
E.
Treuchtlingen
Treuchtlingen is a small town in the Bavarian region of Germany, known for its location in the Altmühl Valley and its role as a local railway junction and spa destination.
- 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_69e0b4f733f081908a401c0b7beb0b9f |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6d058d4dc81908398f8c75e30dc77 |
completed | April 21, 2026, 1:18 a.m. |
Created at: April 16, 2026, 12:46 p.m.