Triple
T7421058
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steven A. Coons Award |
E171245
|
entity |
| Predicate | hasRecipient |
P108
|
FINISHED |
| Object | John Warnock |
E10030
|
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: John Warnock | Statement: [Steven A. Coons Award, hasRecipient, John Warnock]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Warnock Context triple: [Steven A. Coons Award, hasRecipient, John Warnock]
-
A.
John Warnock
chosen
John Warnock was an American computer scientist and co-founder of Adobe Systems, best known for pioneering the PostScript language and the PDF file format.
-
B.
Charles Geschke
Charles Geschke was an American computer scientist and entrepreneur best known as the co-founder of Adobe Systems and a pioneer of desktop publishing technologies.
-
C.
Jef Raskin
Jef Raskin was a human–computer interface expert and computer scientist best known for initiating and leading the early development of Apple’s Macintosh project.
-
D.
Victor Kilian
Victor Kilian was an American character actor known for his prolific work in film and television from the 1920s through the 1970s.
-
E.
Bill Buxton
Bill Buxton is a pioneering computer scientist and designer known for his influential work in human-computer interaction, input technologies, and user experience design.
- 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_69c68a625d048190af70eb8b63bec5a0 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f2ebc520819087cfc2eb9dda0e17 |
completed | March 27, 2026, 9:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c81ef7fc808190a564ab4d9d97ab37 |
completed | March 28, 2026, 6:33 p.m. |
Created at: March 27, 2026, 3:11 p.m.