Triple
T1556721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bernadine Harris |
E33220
|
entity |
| Predicate | laterOccupationInStory |
P19158
|
FINISHED |
| Object | entrepreneur |
—
|
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: entrepreneur | Statement: [Bernadine Harris, laterOccupationInStory, entrepreneur]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterOccupationInStory Context triple: [Bernadine Harris, laterOccupationInStory, entrepreneur]
-
A.
laterCareer
chosen
Indicates that the associated information or events pertain to a later stage or phase in an entity’s professional life or career trajectory.
-
B.
earlierOccupation
Indicates that one occupation held by an entity occurred before another occupation in that entity’s work history.
-
C.
laterPrimaryRole
Indicates that an entity assumes a specified primary role at a later time than another role or state in a sequence.
-
D.
describesCareerOf
Indicates that one entity provides a description or characterization of the professional career of another entity.
-
E.
roleAfterRetirement
Indicates the position, function, or status an entity assumes after it has retired from its previous role or activity.
- 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_69a885ef9cf48190b0af0f5ce3d02231 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a9407d9d1481909597af97b16512cc |
completed | March 5, 2026, 8:36 a.m. |
| PD | Predicate disambiguation | batch_69a907b688d081908171f89010c53973 |
completed | March 5, 2026, 4:33 a.m. |
Created at: March 4, 2026, 7:27 p.m.