Triple
T13691373
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unterallgäu |
E328272
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object | Ottobeuren |
E533648
|
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: Ottobeuren | Statement: [Unterallgäu, containsMunicipality, Ottobeuren]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ottobeuren Context triple: [Unterallgäu, containsMunicipality, Ottobeuren]
-
A.
Ottobeuren
chosen
Ottobeuren is a market town in Bavaria, Germany, best known for its historic Benedictine abbey and impressive Baroque architecture.
-
B.
Sündersbühl
Sündersbühl is a district in Nuremberg, Germany, served by the city’s U3 underground line.
-
C.
Lannesdorf
Lannesdorf is a residential subdistrict of the Bad Godesberg borough in the city of Bonn, Germany.
-
D.
Karlsfeld
Karlsfeld is a municipality in Bavaria, Germany, located just northwest of Munich and known as a suburban residential area with good transport links to the city.
-
E.
Offenberg
Offenberg is a municipality in the Bavarian region of Germany, situated within the Regen district.
- 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_69d8076ff62081908a7bd79889edd7a0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc8746458819095ec1ba3c01ef31b |
completed | April 12, 2026, 4:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7944b93d88190806d6b5735f7e794 |
completed | May 3, 2026, 6:30 p.m. |
Created at: April 9, 2026, 9:53 p.m.