Triple
T22783174
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shether |
E563891
|
entity |
| Predicate | containsCareerInsults |
P43876
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Shether, containsCareerInsults, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsCareerInsults Context triple: [Shether, containsCareerInsults, yes]
-
A.
insultedAs
chosen
Indicates that one entity directed an insulting or offensive remark or action toward another entity, characterizing the target in a demeaning way.
-
B.
supportedCareerOf
Indicates that one entity provided assistance, resources, or endorsement that helped establish or advance another entity’s career.
-
C.
spentEntireCareerWith
Indicates that an individual has worked exclusively for a single organization or team for the full duration of their professional career.
-
D.
associatedWithCareerOf
Indicates a relationship where something is connected or relevant to a person’s professional life, occupation, or career trajectory.
-
E.
managedCareerOf
Indicates that one entity was responsible for overseeing, directing, or handling the professional career of 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_69e2455500788190b4b33030461f3bbd |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17c2ee4e88190951afb2abe69009f |
completed | April 29, 2026, 3:34 a.m. |
| PD | Predicate disambiguation | batch_69eed2c32e8c8190b73bb9965ed47d64 |
completed | April 27, 2026, 3:06 a.m. |
Created at: April 17, 2026, 3:29 p.m.