Triple
T16549569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emma Winsloe |
E402032
|
entity |
| Predicate | stepfatherOccupation |
P5386
|
FINISHED |
| Object | Prime Minister of the United Kingdom |
—
|
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: Prime Minister of the United Kingdom | Statement: [Emma Winsloe, stepfatherOccupation, Prime Minister of the United Kingdom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stepfatherOccupation Context triple: [Emma Winsloe, stepfatherOccupation, Prime Minister of the United Kingdom]
-
A.
stepfatherOf
Indicates that one person is the male spouse or partner of a child's parent, but is not the child's biological or adoptive father.
-
B.
fatherOccupation
Indicates the type of job or profession held by a person's father.
-
C.
stepFatherOfMother
Indicates that one person is the stepfather (non-biological father through marriage) of another person's mother.
-
D.
parentOccupation
chosen
Indicates that one entity has an occupation which is the job or profession of the other entity’s parent.
-
E.
fatherPosition
Indicates the spatial or positional relationship occupied by a father relative to another referenced entity or location.
- 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_69d88384bc30819084229e7dcdc39a41 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e34fc323a88190b5c2a34de0a3c7f0 |
completed | April 18, 2026, 9:32 a.m. |
| PD | Predicate disambiguation | batch_69e2969fab208190ad64164d24748c45 |
completed | April 17, 2026, 8:22 p.m. |
Created at: April 10, 2026, 5:15 a.m.