Triple
T4428776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nuremberg public transport network |
E95272
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Schwabach |
E110122
|
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: Schwabach | Statement: [Nuremberg public transport network, serves, Schwabach]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schwabach Context triple: [Nuremberg public transport network, serves, Schwabach]
-
A.
Schwabach
chosen
Schwabach is a historic town in northern Bavaria, Germany, known for its traditional gold-beating craft and well-preserved old town.
-
B.
Schwabach River
The Schwabach River is a small river in Bavaria, Germany, that flows through the town of Schwabach before joining the Rednitz River.
-
C.
Luterbach
Luterbach is a municipality in the canton of Solothurn in northwestern Switzerland, known for its residential character and proximity to the Aare River.
-
D.
Eschwege
Eschwege is a small historic town in the German state of Hesse, known for its medieval architecture and location near the Werra River.
-
E.
Breitenbach
Breitenbach is a municipality in the canton of Solothurn in northwestern Switzerland, known for its location in the Thierstein district near the French border.
- 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_69b3453c2a0c8190926b574c90766db9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35568767c819084d5e18b56a4745e |
completed | March 13, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b6136ac9c081908780783a27f66474 |
completed | March 15, 2026, 2:03 a.m. |
Created at: March 12, 2026, 11:30 p.m.