Triple
T6588637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stephen Belichick |
E159291
|
entity |
| Predicate | familyOccupation |
P26374
|
FINISHED |
| Object | American football coaching |
—
|
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: American football coaching | Statement: [Stephen Belichick, familyOccupation, American football coaching]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: familyOccupation Context triple: [Stephen Belichick, familyOccupation, American football coaching]
-
A.
siblingOccupation
Indicates that one person has a sibling whose job or profession is the specified occupation.
-
B.
knownRelativesOccupation
chosen
Indicates that there is information about the occupations held by one or more relatives of a given person.
-
C.
parentOccupation
Indicates that one entity has an occupation which is the job or profession of the other entity’s parent.
-
D.
fatherOccupation
Indicates the type of job or profession held by a person's father.
-
E.
subjectOccupation
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
- 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_69c688366ce8819083f8883983c0df92 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6c07cdf048190945ca5810fb1de88 |
completed | March 27, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69c6acfb462481909cb7aff5af4bca9d |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:55 p.m.