Triple
T15966426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GS |
E387202
|
entity |
| Predicate | issuerHasBusinessSegment |
P105459
|
FINISHED |
| Object | Investment Banking |
—
|
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: Investment Banking | Statement: [GS, issuerHasBusinessSegment, Investment Banking]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: issuerHasBusinessSegment Context triple: [GS, issuerHasBusinessSegment, Investment Banking]
-
A.
issuerBusinessType
chosen
Indicates the category or nature of business activity that the issuing entity is engaged in.
-
B.
issuerOwnsBusinessesIn
Indicates that the issuer owns one or more business entities that are located or operate within the specified place.
-
C.
hasBusinessTypeAlong
Indicates that a business or commercial entity located along a route, corridor, or area is associated with a specific type or category of business activity.
-
D.
issuerCustomerType
Indicates the type or category of customer associated with or defined by the issuer.
-
E.
hasBusiness
Indicates that one entity owns, operates, or is formally associated with a business entity.
- 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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e173b3bf6c81909230170e833d7ce7 |
completed | April 16, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69e142d6fb588190b4176eab4bbae774 |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:54 a.m.