Triple
T33877898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shirley Keeldar |
E868404
|
entity |
| Predicate | nameUsageInfluence |
P20713
|
FINISHED |
| Object | helped popularize “Shirley” as a female given name |
—
|
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: helped popularize “Shirley” as a female given name | Statement: [Shirley Keeldar, nameUsageInfluence, helped popularize “Shirley” as a female given name]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nameUsageInfluence Context triple: [Shirley Keeldar, nameUsageInfluence, helped popularize “Shirley” as a female given name]
-
A.
influencedNameOf
chosen
Indicates that one entity has affected or shaped the naming or choice of name of another entity.
-
B.
influenceOf
Indicates that one entity affects, shapes, or alters the state, behavior, or properties of another entity.
-
C.
influentialFrom
Indicates that one entity has exerted influence on another, contributing to or shaping the latter’s ideas, behavior, or development.
-
D.
incorrectInformalUsageOfName
Indicates that one entity uses another entity’s name in an informal context in a way that is considered incorrect or inappropriate.
-
E.
influentialAs
Indicates that one entity has at least as much influence or impact as 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_69f34995b81c8190acdb45cea5a10eff |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7051ad6e4819095e82bbd64761803 |
completed | May 3, 2026, 8:19 a.m. |
| PD | Predicate disambiguation | batch_69f700fe24e08190998e2c96fbaaad38 |
completed | May 3, 2026, 8:02 a.m. |
Created at: May 1, 2026, 1:48 a.m.