Triple
T22427107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Juror (screenplay) |
E554397
|
entity |
| Predicate | writerNotableFor |
P33025
|
FINISHED |
| Object | adaptation of George Dawes Green’s novel |
—
|
LITERAL 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: adaptation of George Dawes Green’s novel | Statement: [The Juror (screenplay), writerNotableFor, adaptation of George Dawes Green’s novel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: writerNotableFor Context triple: [The Juror (screenplay), writerNotableFor, adaptation of George Dawes Green’s novel]
-
A.
notableFor
Indicates that an entity is especially recognized or distinguished for a particular quality, achievement, characteristic, or role.
-
B.
holderNotableFor
chosen
Indicates that a holder (such as a person or organization) is particularly known or recognized for a specific role, achievement, work, or characteristic.
-
C.
notableMaker
Indicates that one entity is a well-known or significant creator, producer, or manufacturer of the other entity.
-
D.
sonNotableFor
Indicates that a son is recognized or distinguished for a particular achievement, role, or characteristic.
-
E.
notableWorkAuthor
Indicates that one entity is the creator or author of a notable work associated with another entity.
- F. None of above.
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_69e11e4f2d0c819091aa3558ea2ee630 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15a2e438481908d43026727afa709 |
completed | April 29, 2026, 1:09 a.m. |
| PD | Predicate disambiguation | batch_69e898a327948190beee5e168006a0a7 |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:47 p.m.