Triple
T21899631
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sarah Marshall |
E540772
|
entity |
| Predicate | settingOfCareer |
P146105
|
FINISHED |
| Object | Hollywood entertainment industry |
—
|
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: Hollywood entertainment industry | Statement: [Sarah Marshall, settingOfCareer, Hollywood entertainment industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingOfCareer Context triple: [Sarah Marshall, settingOfCareer, Hollywood entertainment industry]
-
A.
managedCareerOf
Indicates that one entity was responsible for overseeing, directing, or handling the professional career of another entity.
-
B.
targetCareer
Indicates that one entity is the intended or pursued career or professional goal of another entity.
-
C.
placeInCareer
Indicates the specific role, position, or stage an entity occupies within a person’s professional career.
-
D.
plannedCareer
Indicates that an individual has chosen and intends to pursue a specific career path.
-
E.
settingOfWork
Indicates the place, time, or environment in which a creative work’s narrative or events are situated.
- F. None of above. chosen
Provenance (4 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_69e0c47b4e8c81908c8076eaa4c8e4f2 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f11fca2bf88190b2a5b912aa102513 |
completed | April 28, 2026, 8:59 p.m. |
| PD | Predicate disambiguation | batch_69e6be9a65888190a66598d62d20366c |
completed | April 21, 2026, 12:02 a.m. |
| PDg | Predicate description generation | batch_69e6d054737081908aa7112975b77475 |
completed | April 21, 2026, 1:18 a.m. |
Created at: April 16, 2026, 7:07 p.m.