Triple
T32215730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Computational Learning Theory |
E822917
|
entity |
| Predicate | hasInfluentialResearcher |
P124123
|
FINISHED |
| Object | Leslie Valiant |
—
|
NE NERFINISHED |
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: Leslie Valiant | Statement: [Computational Learning Theory, hasInfluentialResearcher, Leslie Valiant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInfluentialResearcher Context triple: [Computational Learning Theory, hasInfluentialResearcher, Leslie Valiant]
-
A.
hasResearcher
Indicates that an entity is associated with or linked to a specific researcher responsible for work, study, or investigation related to it.
-
B.
hasKeyResearcher
Indicates that an entity is associated with a primary or leading researcher responsible for key research activities related to it.
-
C.
hasInfluentialAuthor
chosen
Indicates that an entity has an author whose work has had significant impact or influence in a relevant domain.
-
D.
hasScientificRole
Indicates that an entity holds or performs a specific scientific position, function, or responsibility in relation to another entity or context.
-
E.
influencedScholar
Indicates that one scholar has had a significant intellectual or academic impact on another scholar’s work, ideas, or development.
- 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_69f3490a3bec819097bc58d4731b9d08 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69ff84202eb081908ae21a54a4414d68 |
completed | May 9, 2026, 6:59 p.m. |
| PD | Predicate disambiguation | batch_69ff833065e4819098579129d4ee17d3 |
completed | May 9, 2026, 6:55 p.m. |
Created at: May 1, 2026, 12:37 a.m.