Triple
T17049859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Main-Tauber-Kreis |
E413663
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Niederstetten |
E1240693
|
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: Niederstetten | Statement: [Main-Tauber-Kreis, contains, Niederstetten]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Niederstetten Context triple: [Main-Tauber-Kreis, contains, Niederstetten]
-
A.
Niederstetten
chosen
Niederstetten is a small town in the Main-Tauber district of Baden-Württemberg, Germany, known for its rural setting and historic architecture.
-
B.
Stetten
Stetten is a locality within the town of Lichtenfels in the German state of Bavaria.
-
C.
Hirschstetten
Hirschstetten is a residential and partly industrial neighborhood in Vienna, Austria, known for its local gardens and suburban character within the district of Donaustadt.
-
D.
Feldstetten
Feldstetten is a village in the Swabian Alb region of Baden-Württemberg, Germany, that forms part of the town of Laichingen.
-
E.
Hochstetten
Hochstetten is a locality within the town of Breisach am Rhein in the Baden-Württemberg region of southwestern Germany.
- 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_69d886cde3d481908d4d01ba88ba7eb7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3daa1aeac81909e8d97bd708c6b71 |
completed | April 18, 2026, 7:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a012341b8e88190a2bee865be5ca1c1 |
completed | May 11, 2026, 12:30 a.m. |
Created at: April 10, 2026, 5:34 a.m.