Triple
T14765716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Francesca Nora Bateman |
E346987
|
entity |
| Predicate | paternalGrandfatherOccupation |
P108948
|
FINISHED |
| Object | film producer |
—
|
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: film producer | Statement: [Francesca Nora Bateman, paternalGrandfatherOccupation, film producer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: paternalGrandfatherOccupation Context triple: [Francesca Nora Bateman, paternalGrandfatherOccupation, film producer]
-
A.
grandfatherOccupation
chosen
Indicates the type of work or profession that a person’s grandfather engaged in.
-
B.
fatherOccupation
Indicates the type of job or profession held by a person's father.
-
C.
paternalGreatGrandfatherOf
Indicates that one person is the father of another person's paternal grandfather.
-
D.
paternalGreatGrandmother
Indicates that one entity is the father’s father’s mother of another entity.
-
E.
maternalGrandmotherOccupation
Indicates the type of job or profession held by a person’s maternal grandmother.
- 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.