Triple
T34888516
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montreal–Quebec City |
E1006216
|
entity |
| Predicate | isMajorPassengerTravelCorridorFor |
P183496
|
FINISHED |
| Object | Quebec |
—
|
NE NERFINISHED |
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: Quebec | Statement: [Montreal–Quebec City, isMajorPassengerTravelCorridorFor, Quebec]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isMajorPassengerTravelCorridorFor Context triple: [Montreal–Quebec City, isMajorPassengerTravelCorridorFor, Quebec]
-
A.
servesPassengerTrafficTo
Indicates that a transportation facility or service provides regular passenger traffic access or operations to a particular location or area.
-
B.
hasCommercialCorridorAlong
Indicates that a place contains a continuous stretch of commercial activity or businesses situated along a specified linear feature, such as a street or route.
-
C.
hasMajorCityOnRoute
Indicates that a major city lies along, or is directly served by, a specified route or path between locations.
-
D.
transportCorridor
Indicates a route or pathway used to move people, goods, or resources between locations.
-
E.
isMajorPassengerRoute
chosen
Indicates that a transportation route serves as a primary corridor carrying a high volume of passenger traffic between locations.
- 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_69f76dbedb288190afe5780710847410 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fdb04ed81c8190b8feea90c1c785a6 |
completed | May 8, 2026, 9:43 a.m. |
| PD | Predicate disambiguation | batch_69fda9d6c5148190a63205b6d9b0a1b4 |
completed | May 8, 2026, 9:16 a.m. |
Created at: May 3, 2026, 4 p.m.