Triple
T15505452
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A46 motorway |
E379068
|
entity |
| Predicate | roadNumber |
P1864
|
FINISHED |
| Object | A46 |
E226847
|
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: A46 | Statement: [A46 motorway, roadNumber, A46]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: A46 Context triple: [A46 motorway, roadNumber, A46]
-
A.
A46
chosen
A46 is a major trunk road in England that runs from Bath in the southwest to Cleethorpes on the east coast, connecting several key cities and regions.
-
B.
A46
The A46 is a major German autobahn in North Rhine-Westphalia that connects several cities in the Ruhr region and Sauerland, facilitating regional east–west traffic.
-
C.
A465
A465 is a major trunk road in Wales that connects several key towns and regions, including the area around Tredegar.
-
D.
A48
The A48 is a major road in South Wales that serves as a key route linking Cardiff with other towns and cities in the region.
-
E.
A45
A45 is a major German autobahn in western Germany that connects the Ruhr area with central regions such as Siegen and Gießen.
- 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_69d85cd53a7c819080f5b9042c4c199e |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03fcd5d948190b25a67a72ef980e9 |
completed | April 16, 2026, 1:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff366bd31c81909e21075b6b601448 |
completed | May 9, 2026, 1:28 p.m. |
Created at: April 10, 2026, 3:55 a.m.