Triple
T26542460
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Upstate Onion Farmer |
E671428
|
entity |
| Predicate | describesOccupationBackground |
P2374
|
FINISHED |
| Object | onion farmer |
—
|
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: onion farmer | Statement: [The Upstate Onion Farmer, describesOccupationBackground, onion farmer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: describesOccupationBackground Context triple: [The Upstate Onion Farmer, describesOccupationBackground, onion farmer]
-
A.
describesCareerOf
Indicates that one entity provides a description or characterization of the professional career of another entity.
-
B.
earlierOccupation
Indicates that one occupation held by an entity occurred before another occupation in that entity’s work history.
-
C.
subjectOccupation
chosen
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
D.
workDescribes
Indicates that one work (such as a document, artwork, or dataset) provides a description or explanatory account of another work.
-
E.
hasPastOccupation
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_69eeb3206e748190b90c85cc81f38c91 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f6691f5e188190b12c7b2eb729a45e |
completed | May 2, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69f66598d6008190a7ca8ff80399fd34 |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 27, 2026, 1:42 a.m.