Triple
T33211415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samuel Sooleymon |
E850171
|
entity |
| Predicate | settingOfCareerDevelopment |
P146105
|
FINISHED |
| Object | United States |
—
|
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: United States | Statement: [Samuel Sooleymon, settingOfCareerDevelopment, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingOfCareerDevelopment Context triple: [Samuel Sooleymon, settingOfCareerDevelopment, United States]
-
A.
settingOfCareer
chosen
Indicates the primary environment, context, or domain in which a person’s career takes place or is situated.
-
B.
careerDevelopment
Indicates a relationship where one entity supports, influences, or engages in the growth, progression, or improvement of another entity’s professional path or skills.
-
C.
developsCareerIn
Indicates that an entity actively builds, advances, or pursues a professional path within a particular field, role, or organization.
-
D.
managedCareerOf
Indicates that one entity was responsible for overseeing, directing, or handling the professional career of another entity.
-
E.
placeInCareer
Indicates the specific role, position, or stage an entity occupies within a person’s professional career.
- 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_69f3495fb92c819083ce65d0ddee7a76 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fbbc49da8c8190902bbb05d2477cab |
completed | May 6, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69fbb13f34b08190bbbb220ac1e6e666 |
completed | May 6, 2026, 9:23 p.m. |
Created at: May 1, 2026, 1:30 a.m.