Triple
T24571689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tinley Park 80th Avenue |
E607977
|
entity |
| Predicate | hasParkingPaymentSystem |
P156391
|
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: [Tinley Park 80th Avenue, hasParkingPaymentSystem, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParkingPaymentSystem Context triple: [Tinley Park 80th Avenue, hasParkingPaymentSystem, yes]
-
A.
hasParking
Indicates that a place or facility provides designated parking space(s) available for use.
-
B.
hasParkingPermitSystem
Indicates that a place or organization operates a system for issuing and managing parking permits for vehicles.
-
C.
hasParkingFor
Indicates that a place or facility provides designated parking spaces suitable for a specified type of vehicle or user.
-
D.
hasParkingConnection
Indicates that one entity is linked to another through a parking-related connection, such as shared access, adjacency, or functional association with parking facilities.
-
E.
parkSystem
Indicates a relationship where an entity is part of, managed by, or associated with an organized system of parks or protected recreational areas.
- F. None of above. chosen
Provenance (4 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_69e2c4cdab6c8190aae6e5d3de55c95e |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2a9257ccc81908efcd9d047772492 |
completed | April 30, 2026, 12:58 a.m. |
| PD | Predicate disambiguation | batch_69f2a6c1f07081908edf0b521767e79b |
completed | April 30, 2026, 12:48 a.m. |
| PDg | Predicate description generation | batch_69f2a846c5bc81909ba50cee483bea91 |
completed | April 30, 2026, 12:54 a.m. |
Created at: April 18, 2026, 2:28 a.m.