Triple
T18856320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Audrey Raines |
E461177
|
entity |
| Predicate | laterFatherOccupation |
P2600
|
FINISHED |
| Object | President of the United States |
—
|
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: President of the United States | Statement: [Audrey Raines, laterFatherOccupation, President of the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterFatherOccupation Context triple: [Audrey Raines, laterFatherOccupation, President of the United States]
-
A.
fatherOccupation
chosen
Indicates the type of job or profession held by a person's father.
-
B.
parentOccupation
Indicates that one entity has an occupation which is the job or profession of the other entity’s parent.
-
C.
fatherPosition
Indicates the spatial or positional relationship occupied by a father relative to another referenced entity or location.
-
D.
fatherWas
Indicates that one entity was the male parent (father) of another entity in the past.
-
E.
sonOccupation
Indicates that a specified occupation is the job or professional role held by a person's son.
- 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_69d8dcfb7b9c8190854e7b171b98ea2e |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c05d0bb8819094d0447441f85b57 |
completed | April 20, 2026, 5:57 a.m. |
| PD | Predicate disambiguation | batch_69e48d2166b88190add38de96cedc65c |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:57 a.m.