Triple
T21190393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Richard C. Levin |
E522195
|
entity |
| Predicate | positionHeld |
P8
|
FINISHED |
| Object | Chief Executive Officer of Coursera |
—
|
NE NERFINISHED |
How this triple was built (3 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: Chief Executive Officer of Coursera | Statement: [Richard C. Levin, positionHeld, Chief Executive Officer of Coursera]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chief Executive Officer of Coursera Context triple: [Richard C. Levin, positionHeld, Chief Executive Officer of Coursera]
-
A.
Executive Director of Khan Academy
The Executive Director of Khan Academy is the chief leader responsible for guiding the nonprofit educational organization’s strategy, operations, and global impact in providing free online learning resources.
-
B.
Chief Executive Officer of Tableau Software
The Chief Executive Officer of Tableau Software is the top executive responsible for leading the data visualization company’s overall strategy, operations, and growth.
-
C.
Chief Executive Officer of Dropbox
The Chief Executive Officer of Dropbox is the top executive responsible for leading the cloud storage and collaboration company’s overall strategy, operations, and growth.
-
D.
Daphne Koller, CEO
Daphne Koller is a computer scientist and entrepreneur best known as the co-founder of Coursera and as a leading figure in applying machine learning to drug discovery.
-
E.
Chief Executive Officer of LinkedIn
The Chief Executive Officer of LinkedIn is the top executive responsible for overseeing the professional networking platform’s global strategy, operations, and growth.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Chief Executive Officer of Coursera Target entity description: The Chief Executive Officer of Coursera is the top executive responsible for leading the global online learning platform’s strategy, operations, and overall growth.
-
A.
Executive Director of Khan Academy
The Executive Director of Khan Academy is the chief leader responsible for guiding the nonprofit educational organization’s strategy, operations, and global impact in providing free online learning resources.
-
B.
Chief Executive Officer of Tableau Software
The Chief Executive Officer of Tableau Software is the top executive responsible for leading the data visualization company’s overall strategy, operations, and growth.
-
C.
Chief Executive Officer of Dropbox
The Chief Executive Officer of Dropbox is the top executive responsible for leading the cloud storage and collaboration company’s overall strategy, operations, and growth.
-
D.
Daphne Koller, CEO
Daphne Koller is a computer scientist and entrepreneur best known as the co-founder of Coursera and as a leading figure in applying machine learning to drug discovery.
-
E.
Chief Executive Officer of LinkedIn
The Chief Executive Officer of LinkedIn is the top executive responsible for overseeing the professional networking platform’s global strategy, operations, and growth.
- F. None of above. chosen
Provenance (2 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_69e0b51061388190aa03f19700d3ef04 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e733372b488190920174955b4b9172 |
completed | April 21, 2026, 8:20 a.m. |
Created at: April 16, 2026, 3:07 p.m.