Triple
T21966456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eric Murphy |
E542470
|
entity |
| Predicate | professionStartContext |
P112203
|
FINISHED |
| Object | begins as manager of Vince Chase's acting career |
—
|
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: begins as manager of Vince Chase's acting career | Statement: [Eric Murphy, professionStartContext, begins as manager of Vince Chase's acting career]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionStartContext Context triple: [Eric Murphy, professionStartContext, begins as manager of Vince Chase's acting career]
-
A.
professionStartLocation
Indicates the place where an individual begins or first takes up their profession or career.
-
B.
careerStartAs
chosen
Indicates the role, position, or occupation in which an individual first began their professional career.
-
C.
careerStart
Indicates the point in time when an entity begins its professional career or main occupational activity.
-
D.
occupationBegan
Indicates the point in time when an entity started holding a particular occupation or job.
-
E.
professionalCategory
Indicates the classification of an entity according to its professional field, role, or occupational domain.
- 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_69e0c47fab1081908dc74a6545dbb051 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1245b821c8190816058c2a07707a3 |
completed | April 28, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69e6f601f2188190893bcdde0cf58ad6 |
completed | April 21, 2026, 3:58 a.m. |
Created at: April 16, 2026, 8:01 p.m.