Triple
T858505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NYSE National |
E18547
|
entity |
| Predicate | feeModel |
P17476
|
FINISHED |
| Object | maker-taker |
—
|
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: maker-taker | Statement: [NYSE National, feeModel, maker-taker]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: feeModel Context triple: [NYSE National, feeModel, maker-taker]
-
A.
costModel
chosen
Indicates the pricing or cost-structure relationship applied to an entity, defining how its costs are calculated or charged.
-
B.
fareBasis
Indicates the specific fare rule or pricing category that applies to a ticket or travel segment.
-
C.
featuresCharge
Indicates that one entity includes, offers, or is characterized by a particular charge (such as a fee, cost, or pricing component).
-
D.
fareType
Indicates the category or class of fare (such as standard, discounted, or promotional) that applies to a given trip, ticket, or pricing instance.
-
E.
fare
Indicates the price or cost required for a person or thing to be transported by a particular mode of travel or service.
- 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_69a4938bdd3c8190a954a3c11844d9cf |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ac4f740881909cb59a6c18a77af3 |
completed | March 1, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69a4aa834a588190bca4a0eb83fb3eb6 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:39 p.m.