Triple
T4978713
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | After Apple-Picking |
E111829
|
entity |
| Predicate | speakerOccupation |
P2374
|
FINISHED |
| Object | apple picker |
—
|
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: apple picker | Statement: [After Apple-Picking, speakerOccupation, apple picker]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: speakerOccupation Context triple: [After Apple-Picking, speakerOccupation, apple picker]
-
A.
namedPersonOccupation
Indicates that a person is explicitly identified as having a particular occupation or job role.
-
B.
sonOccupation
Indicates that a specified occupation is the job or professional role held by a person's son.
-
C.
authorOccupation
Indicates the professional role or job that an author holds or is associated with.
-
D.
sponsorOccupation
Indicates that one entity serves as the occupation or professional role of a sponsor associated with another entity.
-
E.
subjectOccupation
chosen
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
- 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_69bd441adc208190b70a033a0741d01e |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd730a7590819088ab8d49c5c88c2f |
completed | March 20, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69bd7146e6e881908a55ab2756b631f6 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:33 p.m.