Triple
T26907616
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bay Area Express Lanes |
E677297
|
entity |
| Predicate | usesPricingMethod |
P167761
|
FINISHED |
| Object | variable tolls based on congestion |
—
|
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: variable tolls based on congestion | Statement: [Bay Area Express Lanes, usesPricingMethod, variable tolls based on congestion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesPricingMethod Context triple: [Bay Area Express Lanes, usesPricingMethod, variable tolls based on congestion]
-
A.
usesBillingModel
Indicates that one entity applies or operates under a particular billing model for charging or pricing purposes.
-
B.
isValuePriced
Indicates that something is offered at a relatively low or favorable price compared to typical or premium alternatives.
-
C.
hasPriceUnit
Indicates that a price value is expressed in a specific unit of currency or measurement.
-
D.
usesPolicyRate
Indicates that one entity applies or bases its actions or decisions on a specified policy interest rate.
-
E.
priceType
Indicates the classification or category of a price associated with an entity (e.g., list price, sale price, wholesale price).
- 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_69eee9bcef1c8190be88586bb902bb9b |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f66cf092c881908d7034c9c2bc61d5 |
completed | May 2, 2026, 9:30 p.m. |
| PD | Predicate disambiguation | batch_69f66abddc448190a488852f8abdeb2c |
completed | May 2, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69f66c59de9881909ebbb7b0ae7ab495 |
completed | May 2, 2026, 9:27 p.m. |
Created at: April 27, 2026, 6 a.m.