Triple
T145778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alewife station |
E3325
|
entity |
| Predicate | hasParkAndRide |
P1708
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Alewife station, hasParkAndRide, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParkAndRide Context triple: [Alewife station, hasParkAndRide, yes]
-
A.
hasPublicTransportConnection
Indicates that there is an available public transportation link or service connecting the related entities.
-
B.
hasParking
chosen
Indicates that a place or facility provides designated parking space(s) available for use.
-
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.
hasBusInterchange
Indicates that one transport-related entity includes, contains, or is associated with a bus interchange facility.
-
E.
hasParkDistrict
Indicates that an entity is associated with, located within, or administered by a specific park district.
- 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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a257ea7eac8190884a53453a9e0dd6 |
completed | Feb. 28, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69a25656a4fc81908a87678ac3d28f93 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.