Triple
T27116701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ben Warren |
E686868
|
entity |
| Predicate | professionChange |
P71077
|
FINISHED |
| Object | anesthesiology to general surgery |
—
|
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: anesthesiology to general surgery | Statement: [Ben Warren, professionChange, anesthesiology to general surgery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionChange Context triple: [Ben Warren, professionChange, anesthesiology to general surgery]
-
A.
occupationalChange
chosen
Indicates a change in a person’s job, profession, or occupational status over time.
-
B.
professionalCareer
Indicates the relationship capturing a person’s work-related roles, positions, and progression over time in their occupation or field.
-
C.
professionalCategory
Indicates the classification of an entity according to its professional field, role, or occupational domain.
-
D.
managedCareerOf
Indicates that one entity was responsible for overseeing, directing, or handling the professional career of another entity.
-
E.
professionAttribute
Indicates that a specific attribute, quality, or characteristic is associated with a given profession.
- 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_69ef148c2b588190afc15b529f7af845 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f661b58ac48190907b6c6e9ccc2c59 |
completed | May 2, 2026, 8:42 p.m. |
| PD | Predicate disambiguation | batch_69f660eea4648190b0d5e24293607813 |
completed | May 2, 2026, 8:39 p.m. |
Created at: April 27, 2026, 8:57 a.m.