Triple
T34313692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CTA bus 81 Lawrence |
E880519
|
entity |
| Predicate | usesFarePolicy |
P15903
|
FINISHED |
| Object | CTA standard bus fare |
—
|
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: CTA standard bus fare | Statement: [CTA bus 81 Lawrence, usesFarePolicy, CTA standard bus fare]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesFarePolicy Context triple: [CTA bus 81 Lawrence, usesFarePolicy, CTA standard bus fare]
-
A.
farePolicySource
Indicates the origin or authority from which a particular fare policy is derived or defined.
-
B.
usesFareMedium
Indicates that an entity employs a particular fare medium (such as a ticket, card, or pass) as the method of payment or validation for a trip or service.
-
C.
farePolicyType
Indicates the type or category of fare policy that governs how prices, rules, or conditions are applied.
-
D.
farePolicySupport
chosen
Indicates that there is a policy in place governing fares (such as prices, discounts, or rules) that is recognized, enabled, or supported in the given context.
-
E.
usesSingleFareStructure
Indicates that the same fare rules and pricing structure are applied uniformly across all relevant services or routes.
- 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_69f349b8bb6c8190ad12a7957a574f04 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f739a638748190808e7a2930dce16e |
completed | May 3, 2026, 12:03 p.m. |
| PD | Predicate disambiguation | batch_69f732f2dc6c8190a4e86da98cc5eb05 |
completed | May 3, 2026, 11:35 a.m. |
Created at: May 1, 2026, 1:57 a.m.