Triple
T24726758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wyly family |
E618174
|
entity |
| Predicate | knownForCompanyInvolvement |
P152330
|
FINISHED |
| Object | Sterling Software |
—
|
NE NERFINISHED |
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: Sterling Software | Statement: [Wyly family, knownForCompanyInvolvement, Sterling Software]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: knownForCompanyInvolvement Context triple: [Wyly family, knownForCompanyInvolvement, Sterling Software]
-
A.
hasBeenInvolvedIn
Indicates that an entity has participated in, taken part in, or been connected to a particular event, activity, or situation.
-
B.
associatedCompanyKnownFor
chosen
Indicates that a company linked to an entity is recognized or notable for a particular product, service, activity, or characteristic.
-
C.
associatedCompanyNotableRole
Indicates that an entity has a notable role or position in a specified associated company.
-
D.
involvedInWork
Indicates that an entity participates in, contributes to, or is otherwise engaged in a particular work, project, or activity.
-
E.
oftenInvolvedWith
Indicates that one entity frequently participates in or is commonly associated with activities, events, or situations involving another 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_69e2fab772608190b74163751047ff50 |
completed | April 18, 2026, 3:29 a.m. |
| NER | Named-entity recognition | batch_69f44a417a58819081777e18dda149fd |
completed | May 1, 2026, 6:37 a.m. |
| PD | Predicate disambiguation | batch_69f442a977b08190b44eac040cb90211 |
completed | May 1, 2026, 6:05 a.m. |
Created at: April 18, 2026, 3:59 a.m.