Triple
T22170135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter Santos |
E547897
|
entity |
| Predicate | hasFictionalFatherOccupation |
P34569
|
FINISHED |
| Object | United States Congressman |
—
|
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: United States Congressman | Statement: [Peter Santos, hasFictionalFatherOccupation, United States Congressman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalFatherOccupation Context triple: [Peter Santos, hasFictionalFatherOccupation, United States Congressman]
-
A.
hasFictionalFather
Indicates that one entity is the fictional father of another entity.
-
B.
fictionalFatherCharacterPortrayedBy
Indicates that a fictional father character is portrayed or acted by a specific performer or actor.
-
C.
hasFatherFigure
Indicates that one entity serves as a paternal or father-like figure to another entity, regardless of biological relation.
-
D.
fatherOccupation
Indicates the type of job or profession held by a person's father.
-
E.
fictionalOccupation
chosen
Indicates that one entity is the imaginary or narrative-based job, role, or profession attributed to another entity within a fictional context.
- 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_69e11e3c4c5c81908d336165816b12e0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12a67f4dc81909cc5f8d2c1fe6129 |
completed | April 28, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69e71b41555881909b8e22718974d527 |
completed | April 21, 2026, 6:37 a.m. |
Created at: April 16, 2026, 8:34 p.m.