Triple
T13273647
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bank of America Private Bank |
E316130
|
entity |
| Predicate | hasClientSegment |
P70062
|
FINISHED |
| Object | business owners |
—
|
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: business owners | Statement: [Bank of America Private Bank, hasClientSegment, business owners]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasClientSegment Context triple: [Bank of America Private Bank, hasClientSegment, business owners]
-
A.
hasUserSegment
chosen
Indicates that an entity is associated with a particular user segment or group of users defined by shared characteristics or behaviors.
-
B.
hasClient
Indicates that an entity maintains a client relationship with another entity, typically as a provider of goods or services.
-
C.
hasClientGroup
Indicates that an entity is associated with, or belongs to, a particular group of clients.
-
D.
hasSegmentOn
Indicates that one entity includes or occupies a specific segment or portion on another entity (such as a line, path, or sequence).
-
E.
hasSegmentStatus
Indicates that a specific segment within a larger whole is associated with a particular status or condition.
- 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_69d806b1d9ac8190852c5571d5bd5f0f |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f6535688190a5a4549b7be2d611 |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:26 p.m.