Triple
T367122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A35 motorway (France) |
E7984
|
entity |
| Predicate | formsCorridor |
P9789
|
FINISHED |
| Object | north–south transport corridor in eastern France |
—
|
LITERAL 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: north–south transport corridor in eastern France | Statement: [A35 motorway (France), formsCorridor, north–south transport corridor in eastern France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formsCorridor Context triple: [A35 motorway (France), formsCorridor, north–south transport corridor in eastern France]
-
A.
hasCorridor
Indicates that one entity includes, is connected by, or provides access through a corridor to another entity.
-
B.
numberOfCorridors
Indicates the total count of corridors associated with or contained within a given entity or structure.
-
C.
formsFeature
chosen
Indicates that one entity constitutes or creates a characteristic, component, or distinguishing element of another entity.
-
D.
transportCorridor
Indicates a route or pathway used to move people, goods, or resources between locations.
-
E.
formsWith
Indicates that one entity combines or associates with another to create or constitute a joint structure, group, or configuration.
- F. None of above.
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_69a2e7e880008190a6ad7e06e5d03007 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebe92c7c8190b49af2b2b461eacc |
completed | Feb. 28, 2026, 1:21 p.m. |
| PD | Predicate disambiguation | batch_69a2e95ede588190998fdf3a6ea90498 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.