Triple
T32442659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rocket Singh: Salesman of the Year |
E829054
|
entity |
| Predicate | leadCharacterEducation |
P146777
|
FINISHED |
| Object | graduate |
—
|
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: graduate | Statement: [Rocket Singh: Salesman of the Year, leadCharacterEducation, graduate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadCharacterEducation Context triple: [Rocket Singh: Salesman of the Year, leadCharacterEducation, graduate]
-
A.
protagonistEducation
chosen
Indicates the educational background, schooling, or formal training that the protagonist has received.
-
B.
hasEducationCharacteristic
Indicates that an entity possesses a specific educational attribute, quality, or feature (such as level, type, or status of education).
-
C.
educationLevelCharacteristic
Indicates that one entity specifies, describes, or constrains the education level associated with another entity.
-
D.
hasEducationalRole
Indicates that an entity holds a specific function, position, or responsibility within an educational context or setting.
-
E.
didacticCharacter
Indicates that one entity serves a teaching or instructional role toward another, conveying guidance, lessons, or moral instruction.
- 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_69f3491d2e5c819092b1c9535beff8ec |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c2e3d0108190bd5ecee75e662368 |
completed | May 3, 2026, 3:37 a.m. |
| PD | Predicate disambiguation | batch_69f6bd25bed08190befcabd3a41ffadf |
completed | May 3, 2026, 3:12 a.m. |
Created at: May 1, 2026, 12:55 a.m.