Triple
T11222066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rottal-Inn |
E265593
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Eggenfelden |
E259626
|
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: Eggenfelden | Statement: [Rottal-Inn, contains, Eggenfelden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eggenfelden Context triple: [Rottal-Inn, contains, Eggenfelden]
-
A.
Eggenfelden
chosen
Eggenfelden is a town in southeastern Germany known as a local commercial and cultural center within the region of Lower Bavaria.
-
B.
Rottach-Egern
Rottach-Egern is a Bavarian resort town in southern Germany known for its picturesque setting on the shores of Lake Tegernsee and its alpine surroundings.
-
C.
Schneizlreuth
Schneizlreuth is a small Bavarian municipality in southeastern Germany, known for its alpine landscapes and location near the Austrian border.
-
D.
Eberhardzell
Eberhardzell is a rural municipality in the district of Biberach in the German state of Baden-Württemberg.
-
E.
Odelshofen
Odelshofen is a village and district (Ortsteil) of the town of Kehl in the state of Baden-Württemberg, 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_69d6aac59460819089b9848b27f57848 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8ec8fb08190b27144ab65f85957 |
completed | April 9, 2026, 5:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f08f0d9d0c8190a7b84e647c7491e9 |
completed | April 28, 2026, 10:42 a.m. |
Created at: April 8, 2026, 9:30 p.m.