Triple
T27034455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saskia de Jonge |
E681013
|
entity |
| Predicate | hasGenderedOccupation |
P174247
|
FINISHED |
| Object | female swimmer |
—
|
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: female swimmer | Statement: [Saskia de Jonge, hasGenderedOccupation, female swimmer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenderedOccupation Context triple: [Saskia de Jonge, hasGenderedOccupation, female swimmer]
-
A.
endedOccupationOf
Indicates that one entity brought another entity’s occupation or control of a place or position to an end.
-
B.
hasTypicalOccupation
Indicates that an entity commonly or characteristically works in a particular job or profession.
-
C.
representedOccupation
Indicates that one entity has served as an official or formal representative of another entity’s occupation or professional role.
-
D.
requiredOccupationOf
Indicates that one entity specifies the occupation or job role that is required or expected for another entity (such as a position, task, or qualification).
-
E.
commonProfessionAmongBearers
Indicates that multiple entities sharing a given attribute (such as a name or title) are frequently associated with the same profession.
- 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_69eeeb5566f08190813daf896fa3da04 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f6bcc425588190afd0dceba43ed79f |
completed | May 3, 2026, 3:11 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6b1e6c8190adf9d6a257e0b744 |
completed | May 3, 2026, 3 a.m. |
| PDg | Predicate description generation | batch_69f6bbf5a8288190ae170bcbe8ab65cf |
completed | May 3, 2026, 3:07 a.m. |
Created at: April 27, 2026, 7:15 a.m.