Triple
T9728043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | district of Altötting |
E235664
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Neuötting |
E229125
|
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: Neuötting | Statement: [district of Altötting, contains, Neuötting]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Neuötting Context triple: [district of Altötting, contains, Neuötting]
-
A.
Neuötting
chosen
Neuötting is a small Bavarian town in southeastern Germany known for its historic town center and location near the Austrian border.
-
B.
Altötting
Altötting is a Bavarian pilgrimage town renowned as one of Germany’s most important Catholic shrines, centered around the Chapel of Grace and its venerated Black Madonna.
-
C.
Traunreut
Traunreut is a Bavarian town in southeastern Germany known for its industrial base and proximity to the Alpine foothills and Chiemsee lake.
-
D.
Schneizlreuth
Schneizlreuth is a small Bavarian municipality in southeastern Germany, known for its alpine landscapes and location near the Austrian border.
-
E.
Schärding
Schärding is a historic Austrian town on the border with Germany, known for its well-preserved baroque old town and riverside setting.
- 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_69ca84d0fad481909cdd45aa77416c48 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9e7af544819090a8a1adec41943c |
completed | April 1, 2026, 10:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d98801deb8819092a45193078f09b4 |
completed | April 10, 2026, 11:30 p.m. |
Created at: March 30, 2026, 8:21 p.m.