Triple
T28692852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Randall Stephens |
E729331
|
entity |
| Predicate | hasBankingRecords |
P178298
|
FINISHED |
| Object | ledgers |
—
|
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: ledgers | Statement: [Randall Stephens, hasBankingRecords, ledgers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBankingRecords Context triple: [Randall Stephens, hasBankingRecords, ledgers]
-
A.
hasBanking
Indicates that one entity provides or is associated with banking services or facilities for another entity.
-
B.
hasBankUsedFor
Indicates that a financial institution (bank) is utilized for a particular purpose, service, or activity.
-
C.
hasBankOn
Indicates that one entity is located on or alongside the bank (edge) of another entity, typically a river, lake, or similar body.
-
D.
hasBank
Indicates that one entity possesses, is associated with, or is served by a particular bank (such as a financial institution or river bank).
-
E.
hasLoanHistory
Indicates that an entity has a record of past or current loans associated with it.
- 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_69f043e60b6c8190ac2cd042e77fe6e9 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f70e8755a48190931eaa77946f9460 |
completed | May 3, 2026, 8:59 a.m. |
| PD | Predicate disambiguation | batch_69f70abc00848190a1c3f495ef6c8dc6 |
completed | May 3, 2026, 8:43 a.m. |
| PDg | Predicate description generation | batch_69f70e854b9c8190a3416e2189e17742 |
completed | May 3, 2026, 8:59 a.m. |
Created at: April 28, 2026, 5:37 a.m.