Triple
T11994940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Patsy |
E285504
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Stanley E. Johnson |
—
|
NE NERFINISHED |
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: Stanley E. Johnson | Statement: [The Patsy, editedBy, Stanley E. Johnson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stanley E. Johnson Context triple: [The Patsy, editedBy, Stanley E. Johnson]
-
A.
Stanley E. Johnson
Stanley E. Johnson is an editor best known for his work on the classic American children's novel "Old Yeller."
-
B.
Stanley E. Johnson
Stanley E. Johnson is a film editor known for his work on movies such as the comedy feature "The Bellboy."
-
C.
Stanley E. Johnson
chosen
Stanley E. Johnson is a film editor known for his work on the movie "The Ladies Man."
-
D.
Ronald E. Yates
Ronald E. Yates is an American author and former journalist known for his work as a foreign correspondent and as a professor and dean at the University of Illinois’ College of Media.
-
E.
Ronald L. Vaughn
Ronald L. Vaughn is an American academic administrator best known for leading the University of Tampa through significant growth and development as its long-serving president.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6ab44a77c8190a652f4b27164e4ef |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903b211688190bfe6dd15c3f96d2f |
completed | April 10, 2026, 2:05 p.m. |
Created at: April 8, 2026, 9:46 p.m.