Triple
T31675636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Late Show |
E808389
|
entity |
| Predicate | screenplayAwardedFor |
P177588
|
FINISHED |
| Object | Robert Benton |
—
|
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: Robert Benton | Statement: [The Late Show, screenplayAwardedFor, Robert Benton]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: screenplayAwardedFor Context triple: [The Late Show, screenplayAwardedFor, Robert Benton]
-
A.
screenplayAwardedTo
Indicates that a screenplay-related award has been given to a particular recipient.
-
B.
screenplayAwardedBy
Indicates that a screenplay has received an award from a particular awarding body or organization.
-
C.
academyAwardForBestWritingScreenplay
Indicates that an entity received the Academy Award for Best Writing (Screenplay) for a particular film or work.
-
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.
bestOriginalScreenplayWinner
Indicates that the subject is the work (typically a film) that won the award for Best Original Screenplay in a given context or year.
- 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_69f348dcf5d48190ac25b1365ae717a8 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f7009d39508190af7301f824615e88 |
completed | May 3, 2026, 8 a.m. |
| PD | Predicate disambiguation | batch_69f6fc53f4f881908dcc698687bbb64d |
completed | May 3, 2026, 7:42 a.m. |
| PDg | Predicate description generation | batch_69f6ffb7554881908993d6d2ffbcf8f5 |
completed | May 3, 2026, 7:56 a.m. |
Created at: April 30, 2026, 11:02 p.m.