Triple
T34800638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toronto–Montreal |
E1003208
|
entity |
| Predicate | hasSignificantBusinessTravel |
P57247
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Toronto–Montreal, hasSignificantBusinessTravel, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSignificantBusinessTravel Context triple: [Toronto–Montreal, hasSignificantBusinessTravel, true]
-
A.
oftenTravelsWith
Indicates that one entity frequently accompanies another entity when traveling or moving between places.
-
B.
oftenTravelsTo
Indicates that one entity frequently goes to or visits another location or entity.
-
C.
servesBusinessTravel
chosen
Indicates that an entity provides services or accommodations specifically intended for business-related travel.
-
D.
hasTravelType
Indicates the mode or category of travel associated with a given trip, journey, or movement event.
-
E.
hasLongHaulFlights
Indicates that an entity (such as an airline, route, or airport) operates or is associated with long-distance flights typically covering intercontinental or extended-duration journeys.
- 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_69f76db543808190b188c6c86a91491b |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fd974d75e08190af46b1d608769f3b |
completed | May 8, 2026, 7:57 a.m. |
| PD | Predicate disambiguation | batch_69fd94ff792c8190bedf4a639d3da809 |
completed | May 8, 2026, 7:47 a.m. |
Created at: May 3, 2026, 3:59 p.m.