Triple
T38284107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | College Bayside station |
E1022154
|
entity |
| Predicate | servesRidersTravelingAlong |
P42147
|
FINISHED |
| Object | Omni Loop Metromover route |
—
|
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: Omni Loop Metromover route | Statement: [College Bayside station, servesRidersTravelingAlong, Omni Loop Metromover route]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesRidersTravelingAlong Context triple: [College Bayside station, servesRidersTravelingAlong, Omni Loop Metromover route]
-
A.
servesRidersTraveling
chosen
Indicates that a service or entity provides transportation-related service or support to riders who are currently traveling or in transit.
-
B.
servedTravelersBetween
Indicates that an entity provided transportation service for travelers moving between two specified locations.
-
C.
servedByTransportation
Indicates that a location or entity is provided access or connection by a particular mode or service of transportation.
-
D.
servedByRushHourService
Indicates that the entity is provided or operated by a rush hour (peak-time) transit service.
-
E.
servesTravelersTo
Indicates a relationship where one entity provides services, assistance, or accommodations specifically directed toward travelers heading to a particular destination.
- 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_69f76df0cddc81908d16c1556ff4097f |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a00a15604fc8190b1c280794960f3a4 |
completed | May 10, 2026, 3:16 p.m. |
| PD | Predicate disambiguation | batch_6a00a0f7e77881909ac85755ab0e6329 |
completed | May 10, 2026, 3:15 p.m. |
Created at: May 3, 2026, 4:30 p.m.