Triple
T22767207
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fresh Horses |
E563157
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Jane Kurson |
—
|
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: Jane Kurson | Statement: [Fresh Horses, editedBy, Jane Kurson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jane Kurson Context triple: [Fresh Horses, editedBy, Jane Kurson]
-
A.
Jane Kurson
chosen
Jane Kurson is a film editor best known for her work on the 1988 fantasy-comedy film "Beetlejuice."
-
B.
Sheila Nevins
Sheila Nevins is an influential American television producer best known for her long tenure leading HBO’s documentary division and shaping the modern documentary landscape.
-
C.
Diane Mostow
Diane Mostow is a writer known for her work on the television series "Breakdown."
-
D.
Nina Jacobson
Nina Jacobson is an American film and television producer best known as the founder of Color Force and for producing major franchises such as "The Hunger Games."
-
E.
Susan Seidelman
Susan Seidelman is an American film and television director known for her stylish, offbeat comedies and for helping bring independent, female-driven stories into the mainstream in the 1980s.
- 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_69e24552e11c81909c2d61578a558bd7 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17a80e2688190b76844c408929d32 |
completed | April 29, 2026, 3:26 a.m. |
Created at: April 17, 2026, 3:27 p.m.