Triple
T496004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Second Bank of the United States |
E10294
|
entity |
| Predicate | laterInstanceOf |
P14212
|
FINISHED |
| Object | state-chartered bank |
—
|
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: state-chartered bank | Statement: [Second Bank of the United States, laterInstanceOf, state-chartered bank]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterInstanceOf Context triple: [Second Bank of the United States, laterInstanceOf, state-chartered bank]
-
A.
locatedAfter
Indicates that one entity is positioned later than another along a defined sequence, order, or spatial/temporal axis.
-
B.
instanceOf
relation of type constraints
-
C.
tookPlaceAfter
Indicates that one event or occurrence happened later in time than another event or occurrence.
-
D.
namedAfterSince
Indicates that one entity has borne the name of another entity starting from a specific point in time.
-
E.
laterDeployedIn
Indicates that one entity was deployed or put into operation in a particular context, location, or system at a later time than another.
- 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_69a2e847df8481909239ec08ccf1e376 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f115334881908ac5ab96c7f4214e |
completed | Feb. 28, 2026, 1:43 p.m. |
| PD | Predicate disambiguation | batch_69a2edf90ca88190b6a182e5b6733612 |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2eebb2c908190960a4d0c014304cd |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.