Triple
T560494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yoshua Bengio |
E13438
|
entity |
| Predicate | hasResearchInterest |
P934
|
FINISHED |
| Object | probabilistic models |
—
|
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: probabilistic models | Statement: [Yoshua Bengio, hasResearchInterest, probabilistic models]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasResearchInterest Context triple: [Yoshua Bengio, hasResearchInterest, probabilistic models]
-
A.
hasResearchArea
chosen
Indicates that an entity (such as a person, project, or organization) is associated with or focused on a particular field or area of research.
-
B.
hasResearchStatus
Indicates that an entity holds a particular stage or condition within a research process, such as planned, in progress, completed, or published.
-
C.
conductsResearchAt
Indicates that a subject carries out research activities at a specified institution, organization, or location.
-
D.
hasKeyResearcher
Indicates that an entity is associated with a primary or leading researcher responsible for key research activities related to it.
-
E.
hasSubdiscipline
Indicates that one discipline includes another, more specialized field of study as a subordinate branch.
- 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_69a4933edcf08190b35ecfd6014caee6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a499e13694819087a236bffa6601a9 |
completed | March 1, 2026, 7:56 p.m. |
| PD | Predicate disambiguation | batch_69a494befb8481908bb4e2e9f31e343b |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:32 p.m.