Triple
T14764477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sanjay Ghemawat |
E346957
|
entity |
| Predicate | coAuthorWith |
P398
|
FINISHED |
| Object | Jeffrey Dean |
E69556
|
NE 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: Jeffrey Dean | Statement: [Sanjay Ghemawat, coAuthorWith, Jeffrey Dean]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeffrey Dean Context triple: [Sanjay Ghemawat, coAuthorWith, Jeffrey Dean]
-
A.
Jeffrey Dean
chosen
Jeffrey Dean is a prominent American computer scientist and software engineer best known for his influential work on large-scale distributed systems and infrastructure at Google.
-
B.
Jeffery Wood
Jeffery Wood is an American actor best known for his role on the television sitcom "In the House."
-
C.
Brian David Willis
Brian David Willis is a musician best known as a member of the American rock band Quarterflash.
-
D.
Timothy Busfield
Timothy Busfield is an American actor and director best known for his roles in television series such as "thirtysomething," "The West Wing," and various film and stage productions.
-
E.
Michael Culver
Michael Culver is a British actor known for his character roles in film and television, including appearances in productions such as "A Passage to India" and "The Empire Strikes Back."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d822e8896c819091169882f9b20486 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7f3a1608190b1b17624003a0c7f |
completed | April 14, 2026, 11:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe64f0d948819080cc759ca599503d |
completed | May 8, 2026, 10:34 p.m. |
Created at: April 10, 2026, 1:30 a.m.