Triple
T10477688
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rita Coolidge |
E247086
|
entity |
| Predicate | beganCareer |
P67641
|
FINISHED |
| Object | late 1960s |
—
|
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: late 1960s | Statement: [Rita Coolidge, beganCareer, late 1960s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: beganCareer Context triple: [Rita Coolidge, beganCareer, late 1960s]
-
A.
beganAmateurCareer
Indicates that an entity started its amateur-level career or involvement in a particular field or activity.
-
B.
launchedCareerOf
Indicates that one entity’s actions, support, or involvement initiated or significantly advanced another entity’s professional career.
-
C.
startedCareerWith
Indicates that an entity began its professional career associated with, employed by, or active for another specified entity.
-
D.
startTimeOfProfessionalCareer
chosen
Indicates the point in time when an individual’s professional career formally begins.
-
E.
beganModelingCareer
Indicates that an entity started or initiated their professional modeling career at a particular time or under certain circumstances.
- 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_69d381c16c248190a2fe5b471e584e9c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509596a088190895199648ccf91a4 |
completed | April 7, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_69d4fb84bafc8190819757b93620508a |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:21 p.m.