Triple
T23639681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Ladykillers |
E583849
|
entity |
| Predicate | screenplayAwardedTo |
P152991
|
FINISHED |
| Object | William Rose |
—
|
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: William Rose | Statement: [The Ladykillers, screenplayAwardedTo, William Rose]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: screenplayAwardedTo Context triple: [The Ladykillers, screenplayAwardedTo, William Rose]
-
A.
screenplayAwardedBy
Indicates that a screenplay has received an award from a particular awarding body or organization.
-
B.
academyAwardForBestWritingScreenplay
Indicates that an entity received the Academy Award for Best Writing (Screenplay) for a particular film or work.
-
C.
screenplayNominatedWriters
Indicates that the specified writers were nominated for an award for their work on the screenplay of the given film or production.
-
D.
bestAdaptedScreenplayWinner
Indicates that the subject is the work or person that won the award for Best Adapted Screenplay in a given context or event.
-
E.
bestStoryAndScreenplayMusicalOrComedyWinner
Indicates that the subject is the winner of the award for best story and screenplay in the musical or comedy category.
- F. None of above. chosen
Provenance (4 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_69e248fe1c2c8190ac914d2442ff3d26 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b27fc22c8190abda7398b9fb928c |
completed | April 29, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69f118d7903c8190bb590a71771e93af |
completed | April 28, 2026, 8:30 p.m. |
| PDg | Predicate description generation | batch_69f1233300bc8190ac1639bdca1d7d99 |
completed | April 28, 2026, 9:14 p.m. |
Created at: April 17, 2026, 6:48 p.m.