Triple
T26781012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Autoroute 440 (Laval) |
E670244
|
entity |
| Predicate | hasJunctionOrientation |
P162820
|
FINISHED |
| Object | north–south connectors |
—
|
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 connectors | Statement: [Autoroute 440 (Laval), hasJunctionOrientation, north–south connectors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasJunctionOrientation Context triple: [Autoroute 440 (Laval), hasJunctionOrientation, north–south connectors]
-
A.
hasJunctionWith
Indicates that one entity meets or intersects with another at a shared junction point.
-
B.
hasJunctionType
Indicates the specific kind or classification of a junction associated with an entity.
-
C.
hasJunctionCount
Indicates the number of junctions associated with or contained in a given entity.
-
D.
hasJunctionIn
Indicates that one entity contains or includes a junction located within the spatial or structural extent of another entity.
-
E.
isJunction
Indicates that an entity functions as a junction point where multiple paths, lines, or connections meet or intersect.
- F. None of above. chosen
Provenance (4 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_69eeb31c925881909b597f6e40056d28 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f62e4168a48190b45268f922780da6 |
completed | May 2, 2026, 5:02 p.m. |
| PD | Predicate disambiguation | batch_69f62c15952881908a5ea0c25904afec |
completed | May 2, 2026, 4:53 p.m. |
| PDg | Predicate description generation | batch_69f62d5268ac8190835dc7119353b840 |
completed | May 2, 2026, 4:58 p.m. |
Created at: April 27, 2026, 4:09 a.m.