Triple
T21755813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VanShare |
E537035
|
entity |
| Predicate | typicalTripSegment |
P60863
|
FINISHED |
| Object | between transit hubs and workplaces |
—
|
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: between transit hubs and workplaces | Statement: [VanShare, typicalTripSegment, between transit hubs and workplaces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalTripSegment Context triple: [VanShare, typicalTripSegment, between transit hubs and workplaces]
-
A.
transportSegment
chosen
Indicates a distinct portion of a larger journey or route during which something or someone is transported from one point to another.
-
B.
crewTransportSegment
Indicates a segment of a journey during which crew members are transported from one location to another.
-
C.
airlineMarketSegment
Indicates a relationship where an airline is associated with a specific market segment it targets or operates within (e.g., business, leisure, regional).
-
D.
hasTourLeg
Indicates that a specific segment or leg is part of, or associated with, a larger tour or journey.
-
E.
involvedTravelBetween
Indicates a relationship where an entity participates in or is associated with travel occurring between two specified 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_69e0c46eab808190b848242d63a17c47 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f01d8ea04c8190a8c4fa43b3f23935 |
completed | April 28, 2026, 2:38 a.m. |
| PD | Predicate disambiguation | batch_69e6969e46088190b13d6e9025775ea3 |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:50 p.m.