Triple
T14765719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Francesca Nora Bateman |
E346987
|
entity |
| Predicate | paternalAuntOccupation |
P112082
|
FINISHED |
| Object | actress |
—
|
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: actress | Statement: [Francesca Nora Bateman, paternalAuntOccupation, actress]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: paternalAuntOccupation Context triple: [Francesca Nora Bateman, paternalAuntOccupation, actress]
-
A.
auntOccupation
chosen
Indicates that an individual’s aunt holds or performs a particular occupation or job.
-
B.
paternalUncleInstanceOf
Indicates that one entity is a specific instance of the paternal uncle relationship to another entity (i.e., the brother of the person's father).
-
C.
knownRelativesOccupation
Indicates that there is information about the occupations held by one or more relatives of a given person.
-
D.
fatherOccupation
Indicates the type of job or profession held by a person's father.
-
E.
maternalAuntOrUncle
Indicates that one person is the sibling of another person's mother, regardless of the sibling's gender.
- 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_69d822e8896c819091169882f9b20486 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7f576c881909da70627f5897c94 |
completed | April 14, 2026, 11:04 p.m. |
| PD | Predicate disambiguation | batch_69de8c02e5c08190943c27594026faf7 |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:30 a.m.