Triple
T2247141
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A86 autoroute |
E49528
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | A86 motorway |
E346811
|
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: A86 motorway | Statement: [A86 autoroute, alsoKnownAs, A86 motorway]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: A86 motorway Context triple: [A86 autoroute, alsoKnownAs, A86 motorway]
-
A.
A86 motorway
chosen
The A86 motorway is a major orbital highway forming part of the ring road system around Paris, France.
-
B.
A81 motorway
The A81 motorway is a major German autobahn running through the state of Baden-Württemberg, forming an important north–south transport corridor.
-
C.
A9 motorway
The A9 motorway is a major French highway in southern France that connects cities near the Mediterranean coast and serves as an important route between Spain and the rest of Europe.
-
D.
A106 motorway
The A106 motorway is a short French autoroute in the southern suburbs of Paris that provides direct road access between Paris and Paris Orly Airport.
-
E.
A6 motorway
The A6 motorway is a major French highway that forms part of the main route between Paris and Lyon, serving as a key corridor through central and eastern France.
- 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_69a88aa979788190ad6500f1d8eee2fc |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc0ec46b08190ae12de8b255eb71d |
completed | March 7, 2026, 6:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b324b9ba9c8190bfba5d7539cffeb2 |
completed | March 12, 2026, 8:40 p.m. |
Created at: March 4, 2026, 7:47 p.m.