Triple
T22819709
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AdaGrad |
E565192
|
entity |
| Predicate | proposedBy |
P32
|
FINISHED |
| Object |
John Duchi
John Duchi is a computer scientist and statistician known for his influential work in optimization, machine learning, and statistical learning theory.
|
E1555009
|
NE FINISHED |
How this triple was built (4 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: John Duchi | Statement: [AdaGrad, proposedBy, John Duchi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Duchi Context triple: [AdaGrad, proposedBy, John Duchi]
-
A.
Bernard Beame
Bernard Beame is known primarily as the son of Abraham Beame, the former mayor of New York City.
-
B.
Mike Hanrahan
Mike Hanrahan is an entrepreneur and technology executive best known as a co-founder of the e-commerce company Jet.com.
-
C.
Mark Healey
Mark Healey is a British video game designer best known as a co-founder of Media Molecule and the creative director behind the acclaimed game LittleBigPlanet.
-
D.
Michael W. Watters
Michael W. Watters is an editor known for his work on the rock opera film "Repo! The Genetic Opera."
-
E.
John Donnelly
John Donnelly is a British playwright and screenwriter known for his work in contemporary theatre and television, including the adaptation of the play "The Pass."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: John Duchi Triple: [AdaGrad, proposedBy, John Duchi]
Generated description
John Duchi is a computer scientist and statistician known for his influential work in optimization, machine learning, and statistical learning theory.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: John Duchi Target entity description: John Duchi is a computer scientist and statistician known for his influential work in optimization, machine learning, and statistical learning theory.
-
A.
Bernard Beame
Bernard Beame is known primarily as the son of Abraham Beame, the former mayor of New York City.
-
B.
Mike Hanrahan
Mike Hanrahan is an entrepreneur and technology executive best known as a co-founder of the e-commerce company Jet.com.
-
C.
Mark Healey
Mark Healey is a British video game designer best known as a co-founder of Media Molecule and the creative director behind the acclaimed game LittleBigPlanet.
-
D.
Michael W. Watters
Michael W. Watters is an editor known for his work on the rock opera film "Repo! The Genetic Opera."
-
E.
John Donnelly
John Donnelly is a British playwright and screenwriter known for his work in contemporary theatre and television, including the adaptation of the play "The Pass."
- F. None of above. chosen
Provenance (5 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_69e2458426188190b58b8ab4844fe420 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17dcf39a88190bec26affc304236d |
completed | April 29, 2026, 3:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b9ea869348190b4c8edc9f8b5dbc3 |
completed | May 18, 2026, 11:20 p.m. |
| NEDg | Description generation | batch_6a0b9f9c46988190baeb6f4e1ec2a419 |
completed | May 18, 2026, 11:24 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0ba068def08190b22058cf5bd76b4f |
completed | May 18, 2026, 11:27 p.m. |
Created at: April 17, 2026, 3:33 p.m.