Triple
T14137749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Susan Kare |
E350341
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Susan Kare |
E350341
|
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: Susan Kare | Statement: [Susan Kare, name, Susan Kare]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Susan Kare Context triple: [Susan Kare, name, Susan Kare]
-
A.
Susan Kare
chosen
Susan Kare is a pioneering graphic designer best known for creating many of the original icons, typefaces, and interface elements for the early Apple Macintosh.
-
B.
Victor Kilian
Victor Kilian was an American character actor known for his prolific work in film and television from the 1920s through the 1970s.
-
C.
Chip Kidd
Chip Kidd is an acclaimed American graphic designer and author best known for his influential and inventive book cover designs.
-
D.
Bruce Degen
Bruce Degen is an American illustrator and children's book author best known for his artwork in the popular educational series "The Magic School Bus."
-
E.
Philip Stark
Philip Stark is an American screenwriter best known for writing the comedy film "Dude, Where's My Car?".
- 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_69d827865f608190b311820428ae027b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de610fb86c81909eb26bf9c13696ca |
completed | April 14, 2026, 3:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcdf16079c819080a74cd8a6eb37a6 |
completed | May 7, 2026, 6:51 p.m. |
Created at: April 10, 2026, 12:38 a.m.