Triple
T4933482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pulaski station (CTA Orange Line) |
E110751
|
entity |
| Predicate | hasTurnstiles |
P1973
|
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: [Pulaski station (CTA Orange Line), hasTurnstiles, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTurnstiles Context triple: [Pulaski station (CTA Orange Line), hasTurnstiles, yes]
-
A.
hasEntrance
Indicates that one entity possesses or provides an entry point or access way to another entity or space.
-
B.
hasEntranceControl
Indicates that an entity implements or is subject to mechanisms that regulate or control access to its entrance.
-
C.
hasNumberOfEntrances
Indicates the relationship that specifies how many entrances an entity possesses.
-
D.
hasFaregates
chosen
Indicates that an entity is equipped with or contains faregates used to control or validate access, typically for paid entry.
-
E.
hasTicketInspection
Indicates that a ticket is checked or verified by an authorized inspector or system.
- 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_69bd4415190c8190817bee7ec9f9f944 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd70652d988190ba4a493db510952e |
completed | March 20, 2026, 4:05 p.m. |
| PD | Predicate disambiguation | batch_69bd6c3695c8819094e7ad2f6d4ba1ac |
completed | March 20, 2026, 3:48 p.m. |
Created at: March 20, 2026, 1:30 p.m.