Triple
T12765674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montpellier tramway |
E305115
|
entity |
| Predicate | hasRouteLayout |
P10827
|
FINISHED |
| Object | radial and circular lines |
—
|
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: radial and circular lines | Statement: [Montpellier tramway, hasRouteLayout, radial and circular lines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRouteLayout Context triple: [Montpellier tramway, hasRouteLayout, radial and circular lines]
-
A.
hasRoute
Indicates that there exists a path or connection enabling travel or communication from one entity to another.
-
B.
hasRouteType
Indicates that there is a specific kind or category of route associated with an entity (e.g., road, rail, bus line).
-
C.
hasRouteAlignment
Indicates that there is a defined spatial or geometric alignment associated with a route or pathway.
-
D.
hasLayout
chosen
Indicates that one entity defines or is associated with the structural arrangement or organization (layout) of another entity.
-
E.
hasRouteFeature
Indicates that a route possesses or is associated with a specific characteristic, attribute, or feature.
- 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_69d7bdf1fcd081909ffb0e0d6fa3a07d |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96df1ef148190af525532fcb0933b |
completed | April 10, 2026, 9:38 p.m. |
| PD | Predicate disambiguation | batch_69d96409739881909174ba005a986cb5 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:28 p.m.