Triple
T2764498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LaGuardia Airport |
E61301
|
entity |
| Predicate | hasSurfaceTransportConnection |
P1298
|
FINISHED |
| Object | bus |
—
|
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: bus | Statement: [LaGuardia Airport, hasSurfaceTransportConnection, bus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSurfaceTransportConnection Context triple: [LaGuardia Airport, hasSurfaceTransportConnection, bus]
-
A.
hasPublicTransportConnection
Indicates that there is an available public transportation link or service connecting the related entities.
-
B.
hasTransportRoute
Indicates that there exists a designated transportation connection or route linking one entity to another.
-
C.
hasTransportHub
Indicates that a location contains or serves as a central facility where multiple transport routes or modes connect for passenger or cargo movement.
-
D.
hasUndergroundConnections
Indicates that one entity is linked to another through subterranean or hidden passageways, networks, or channels.
-
E.
hasGroundTransportation
chosen
Indicates that an entity provides, includes, or is connected to transportation services or options that operate on land (e.g., cars, buses, trains).
- 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_69ab4b7bab6c8190a5c2efef19a8ef34 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abddceb9d88190961e30d521a21552 |
completed | March 7, 2026, 8:11 a.m. |
| PD | Predicate disambiguation | batch_69abdcfc5e1c8190a5ac2c48d3eaeb0a |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:57 p.m.