Triple
T17241962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tübingen region |
E418520
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Ulm (city) |
E9969
|
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: Ulm (city) | Statement: [Tübingen region, contains, Ulm (city)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ulm (city) Context triple: [Tübingen region, contains, Ulm (city)]
-
A.
Ulm
chosen
Ulm is a historic city in the German state of Baden-Württemberg, best known for its towering Gothic cathedral and as the birthplace of physicist Albert Einstein.
-
B.
Neu-Ulm
Neu-Ulm is a Bavarian town in southern Germany located across the Danube River from the city of Ulm, forming a closely linked urban area with it.
-
C.
Günzburg
Günzburg is a small Bavarian town in southern Germany, historically notable as the birthplace of Nazi physician Josef Mengele.
-
D.
Reutlingen
Reutlingen is a city in southwestern Germany known for its location at the foot of the Swabian Jura and its well-preserved medieval old town.
-
E.
Kaufbeuren
Kaufbeuren is a historic Bavarian town in southern Germany known for its well-preserved medieval old town and traditional Swabian culture.
- 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_69d886d8e96081909870bff6c3d0bf09 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42e21003c81908c884a3c8712676a |
completed | April 19, 2026, 1:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01794102348190ba5906c011fd014b |
completed | May 11, 2026, 6:37 a.m. |
Created at: April 10, 2026, 5:39 a.m.