Triple
T9440790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Augsburg district |
E227639
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Bobingen |
E783728
|
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: Bobingen | Statement: [Augsburg district, contains, Bobingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bobingen Context triple: [Augsburg district, contains, Bobingen]
-
A.
Bobingen
chosen
Bobingen is a small town in Bavaria, Germany, situated near Augsburg and known for its location along the Wertach River.
-
B.
Böbing
Böbing is a small municipality in the Weilheim-Schongau district of Bavaria, Germany, known for its rural setting in the Alpine foothills.
-
C.
Boblingen
Böblingen is a town in the German state of Baden-Württemberg, known for its automotive industry presence and proximity to Stuttgart.
-
D.
Brieg
Brieg is a historic town in southwestern Poland, known today as Brzeg, that was formerly part of Germany’s Silesia region.
-
E.
Waidberg
Waidberg is a wooded hill and recreational area on the outskirts of Zurich, Switzerland, known for its hiking trails, viewpoints, and proximity to the Hönggerberg.
- 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_69ca843884488190ad6cbe0153088234 |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7ee4f4a08190ada5ee14fec2b822 |
completed | April 1, 2026, 8:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d18208ba9081909efa44f98f90c11a |
completed | April 4, 2026, 9:26 p.m. |
Created at: March 30, 2026, 7:50 p.m.