Triple
T30368854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Los Angeles Metro fare system |
E772496
|
entity |
| Predicate | fareInspectionMethod |
P169128
|
FINISHED |
| Object | proof-of-payment on rail |
—
|
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: proof-of-payment on rail | Statement: [Los Angeles Metro fare system, fareInspectionMethod, proof-of-payment on rail]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fareInspectionMethod Context triple: [Los Angeles Metro fare system, fareInspectionMethod, proof-of-payment on rail]
-
A.
fareModel
Indicates a pricing relationship where a specific fare structure, rule set, or calculation method is applied to determine the cost of a trip or service.
-
B.
fareControlUnifiedWith
Indicates that separate fare control areas are combined into a single, shared fare-controlled zone.
-
C.
fareType
Indicates the category or class of fare (such as standard, discounted, or promotional) that applies to a given trip, ticket, or pricing instance.
-
D.
fareRequired
Indicates that a payment or fare is required for access to or use of a service, route, or transportation option.
-
E.
fareBasis
Indicates the specific fare rule or pricing category that applies to a ticket or travel segment.
- 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_69f2248d71408190aec0d5c2001b1cff |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f682825f408190b6510f20015c4e52 |
completed | May 2, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69f678d019fc8190913662cd2f87b857 |
completed | May 2, 2026, 10:21 p.m. |
| PDg | Predicate description generation | batch_69f679496c188190ba585792f987a1f4 |
completed | May 2, 2026, 10:23 p.m. |
Created at: April 29, 2026, 7:59 p.m.