Triple
T7064956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bundesstraße 28 |
E164322
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Neu-Ulm |
E177294
|
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: Neu-Ulm | Statement: [Bundesstraße 28, passesThrough, Neu-Ulm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Neu-Ulm Context triple: [Bundesstraße 28, passesThrough, Neu-Ulm]
-
A.
Neu-Ulm
chosen
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.
-
B.
Landsberg am Lech
Landsberg am Lech is a historic Bavarian town in southern Germany known for its medieval old town, picturesque setting on the Lech River, and its association with the nearby Landsberg Prison.
-
C.
Backnang
Backnang is a town in the German state of Baden-Württemberg, located northeast of Stuttgart and known for its historical center and role as a regional industrial and commuter hub.
-
D.
Kaufbeuren
Kaufbeuren is a historic Bavarian town in southern Germany known for its well-preserved medieval old town and traditional Swabian culture.
-
E.
Rosenheim
Rosenheim is a town in Upper Bavaria, Germany, known as a regional economic and transportation hub near the Alps.
- 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_69c688796c148190adb2f1596f595f22 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e4a3c36c819080942c59f1830ae8 |
completed | March 27, 2026, 8:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc931ce9b081908a58fb3a54492e60 |
completed | April 1, 2026, 3:38 a.m. |
Created at: March 27, 2026, 2:39 p.m.