Triple
T16194888
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bay Fair station |
E393035
|
entity |
| Predicate | hasParkingLotLighting |
P1280
|
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: [Bay Fair station, hasParkingLotLighting, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParkingLotLighting Context triple: [Bay Fair station, hasParkingLotLighting, yes]
-
A.
hasRunwayLighting
Indicates that a runway is equipped with lighting systems to aid visibility and operations, typically during low-light or night conditions.
-
B.
hasParking
Indicates that a place or facility provides designated parking space(s) available for use.
-
C.
hasParkingLotOwner
Indicates that a parking lot is owned or possessed by a specific owner.
-
D.
hasUndergroundParking
Indicates that a place or building provides parking facilities located below ground level.
-
E.
hasLighting
chosen
Indicates that one entity is equipped with, contains, or is characterized by a particular type or configuration of lighting.
- 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_69d87f1e49ac8190a311b54d32990576 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e222d851188190b2452d165e4fc4bd |
completed | April 17, 2026, 12:08 p.m. |
| PD | Predicate disambiguation | batch_69e219e11f6081909106b1240a17fd37 |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:02 a.m.