Triple
T15980794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Réseau de transport de la Capitale |
E387564
|
entity |
| Predicate | hasRouteNetworkType |
P23132
|
FINISHED |
| Object | urban bus 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: urban bus network | Statement: [Réseau de transport de la Capitale, hasRouteNetworkType, urban bus network]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRouteNetworkType Context triple: [Réseau de transport de la Capitale, hasRouteNetworkType, urban bus network]
-
A.
hasRouteNetwork
Indicates that one entity possesses, is associated with, or is covered by a specific route network connecting multiple locations or paths.
-
B.
routeNetworkType
chosen
Indicates the specific kind of transportation or communication network to which a route belongs (e.g., road, rail, or air).
-
C.
hasRouteType
Indicates that there is a specific kind or category of route associated with an entity (e.g., road, rail, bus line).
-
D.
hasRoadNetworkType
Indicates the type or classification of road network associated with or present in an entity.
-
E.
trailNetworkType
Indicates the classification of a trail within a broader trail network, such as its role, category, or type of route in that system.
- 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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4d08f481909f38b75e3f42d9ab |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142d9d8e881909b559a3e3ca21d24 |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:54 a.m.