Triple
T12644185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A104 autoroute |
E301977
|
entity |
| Predicate | hasJunctionWith |
P1018
|
FINISHED |
| Object | A3 autoroute |
E822936
|
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: A3 autoroute | Statement: [A104 autoroute, hasJunctionWith, A3 autoroute]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: A3 autoroute Context triple: [A104 autoroute, hasJunctionWith, A3 autoroute]
-
A.
A3 autoroute
The A3 autoroute is a short French motorway in the Île-de-France region that connects Paris to its northeastern suburbs and links major radial routes around the capital.
-
B.
Autoroute A3
chosen
Autoroute A3 is a short French motorway in the Île-de-France region that connects Paris to its northeastern suburbs and links with major routes such as the A1 and A86.
-
C.
A103 autoroute
The A103 autoroute is a short French motorway in the eastern suburbs of Paris that links local traffic to the larger national autoroute network.
-
D.
A13 autoroute
The A13 autoroute is a major French motorway linking Paris to Normandy, serving as a key route toward cities such as Rouen and Caen.
-
E.
A1 autoroute
The A1 autoroute is a major French motorway connecting Paris to Lille and serving key locations such as Charles de Gaulle Airport and the northern suburbs.
- 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_69d7bdec9f9c8190b4bac675b7588211 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9614bf2f881909976becdf747f4fb |
completed | April 10, 2026, 8:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6fef8d94081908ea5ac426e22ef87 |
completed | May 3, 2026, 7:53 a.m. |
Created at: April 9, 2026, 5:17 p.m.