Triple
T17077403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dunstable, Bedfordshire, England |
E414385
|
entity |
| Predicate | roadConnection |
P385
|
FINISHED |
| Object | A5 |
E424364
|
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: A5 | Statement: [Dunstable, Bedfordshire, England, roadConnection, A5]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: A5 Context triple: [Dunstable, Bedfordshire, England, roadConnection, A5]
-
A.
A5
A5 is a major Swiss motorway that connects key regions in the northwest of the country, facilitating traffic between cities such as Solothurn, Biel/Bienne, and Neuchâtel.
-
B.
A5
A5 is a major German autobahn running north–south through western Germany, connecting cities such as Hattenbach, Frankfurt, and Basel.
-
C.
A5
A5 is a major Italian motorway connecting the city of Turin with the Aosta Valley and the Mont Blanc Tunnel at the French border.
-
D.
A5
A5 is a major French autoroute that connects the Paris region to the east of the country, serving as an important long-distance traffic corridor.
-
E.
A5
chosen
The A5 is a major road in the United Kingdom that historically follows the route of the Roman Watling Street, linking London with the Midlands and North Wales.
- 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_69d886cef44c8190ba56c44b4e863e64 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dbc625c48190b679a521180e10ad |
completed | April 18, 2026, 7:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a012edfda588190aff6c6d4c8d64ddd |
completed | May 11, 2026, 1:20 a.m. |
Created at: April 10, 2026, 5:34 a.m.