Triple
T6970388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Electronic Funds Transfer system |
E161583
|
entity |
| Predicate | supportsCustomerType |
P55187
|
FINISHED |
| Object | individual customers |
—
|
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: individual customers | Statement: [National Electronic Funds Transfer system, supportsCustomerType, individual customers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsCustomerType Context triple: [National Electronic Funds Transfer system, supportsCustomerType, individual customers]
-
A.
supportsUserType
chosen
Indicates that one entity is compatible with, or provides functionality for, a specified type or category of user.
-
B.
supportsParticipantType
Indicates that an entity is compatible with, or designed to work with, a specified type or category of participant.
-
C.
supportsAccountType
Indicates that one entity is compatible with, or able to operate for, a specified type or category of account.
-
D.
supportsType
Indicates that one entity is capable of handling, accepting, or being compatible with a specified type.
-
E.
supportsGuest
Indicates that one entity provides assistance, resources, or accommodation to another entity in the role of a guest.
- 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_69c68854a0d88190bc0bf82263f1afce |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6db1649288190a52c7dab57b3c7dc |
completed | March 27, 2026, 7:31 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c262508190a7708b3d9cf23d7c |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:30 p.m.