Triple
T10397627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | European route E54 |
E245060
|
entity |
| Predicate | hasRouteSegmentIn |
P51968
|
FINISHED |
| Object | French road network |
—
|
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: French road network | Statement: [European route E54, hasRouteSegmentIn, French road network]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRouteSegmentIn Context triple: [European route E54, hasRouteSegmentIn, French road network]
-
A.
hasSegmentOn
chosen
Indicates that one entity includes or occupies a specific segment or portion on another entity (such as a line, path, or sequence).
-
B.
hasRoute
Indicates that there exists a path or connection enabling travel or communication from one entity to another.
-
C.
hasComponentRoute
Indicates that one route includes another route as a constituent or subordinate part of its overall structure.
-
D.
routeSegment
Indicates a specific portion of a larger route that directly connects two points or locations within that route.
-
E.
hasRouteStart
Indicates that one entity serves as the starting point or origin location for a specified route associated with another entity.
- 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_69d381b5116081908d85227bab6d3c0c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9d0de448190b0bfd4d6c87d47fa |
completed | April 7, 2026, 11:26 a.m. |
| PD | Predicate disambiguation | batch_69d4dfb438c481908dff87c47de2f069 |
completed | April 7, 2026, 10:43 a.m. |
Created at: April 6, 2026, 12:07 p.m.