Triple
T6713024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kerpen |
E153193
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | A4 motorway |
E376897
|
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: A4 motorway | Statement: [Kerpen, locatedNear, A4 motorway]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: A4 motorway Context triple: [Kerpen, locatedNear, A4 motorway]
-
A.
A4 motorway
The A4 motorway is a major Dutch highway that connects key cities including Amsterdam, The Hague, and Rotterdam, forming part of the European route network.
-
B.
A4 motorway
chosen
The A4 motorway is a major German autobahn running east–west across central Germany, connecting cities such as Aachen, Cologne, Erfurt, Jena, and Dresden.
-
C.
A4 motorway
The A4 motorway is a major Italian highway running across northern Italy, connecting key cities such as Turin, Milan, Verona, Vicenza, and Venice.
-
D.
A4 motorway
The A4 motorway is a major French highway connecting Paris to the eastern regions of France and onward toward Germany, serving as a key commuter and long-distance route.
-
E.
A4 motorway
The A4 motorway is a major Portuguese highway that connects Porto to the country’s northeastern interior, improving access to regions such as Vila Real and Bragança.
- 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_69c68809b4608190a2509ddb5ab87f05 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d121a92c8190a03f384a8aba84da |
completed | March 27, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1aef47b908190a7aff84fbf2759db |
completed | April 5, 2026, 12:38 a.m. |
Created at: March 27, 2026, 2:07 p.m.