Triple
T33552048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rosie Richardson |
E859362
|
entity |
| Predicate | occupationBeforeStory |
P107616
|
FINISHED |
| Object | media worker |
—
|
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: media worker | Statement: [Rosie Richardson, occupationBeforeStory, media worker]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: occupationBeforeStory Context triple: [Rosie Richardson, occupationBeforeStory, media worker]
-
A.
earlierOccupation
Indicates that one occupation held by an entity occurred before another occupation in that entity’s work history.
-
B.
hasOccupationDuringStory
Indicates that an entity holds or performs a particular occupation or job role during the time span covered by the story.
-
C.
economicRolePast
Indicates that an entity previously held a specific economic function, position, or role in the past.
-
D.
characterFormerOccupation
Indicates that a character previously held a specific occupation but no longer does.
-
E.
hasPastOccupation
chosen
Indicates that an entity previously held a particular job, role, or occupation in the past.
- 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_69f3497b2b68819093207971b5e13dc8 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6f70c17d88190aa74afc2dd2a0467 |
completed | May 3, 2026, 7:19 a.m. |
| PD | Predicate disambiguation | batch_69f6f6632dfc8190af85e258c8519207 |
completed | May 3, 2026, 7:16 a.m. |
Created at: May 1, 2026, 1:39 a.m.