Triple
T38545876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Styne and Cahn |
E924960
|
entity |
| Predicate | roleOfJuleStyne |
P193518
|
FINISHED |
| Object | composer |
—
|
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: composer | Statement: [Styne and Cahn, roleOfJuleStyne, composer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleOfJuleStyne Context triple: [Styne and Cahn, roleOfJuleStyne, composer]
-
A.
roleInTheGrandBudapestHotel
Indicates that an entity has a specific role or part in the context of "The Grand Budapest Hotel" (such as a character, performer, or production role).
-
B.
roleOfGracieAllen
Indicates that the specified role or function is performed or held by Gracie Allen.
-
C.
MaryAstorRole
Indicates that an entity represents a role or character portrayed by Mary Astor in a film, play, or other performance.
-
D.
roleInTheMarvelousMrsMaisel
Indicates that an entity has a role or appearance in the television series "The Marvelous Mrs. Maisel."
-
E.
roleInMadMen
Indicates that one entity has a specific role or character in the television series "Mad Men" in relation to another entity.
- 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_69f76eadeac081909cdfdd0474cb6765 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fd485f57dc8190820365396d041991 |
completed | May 8, 2026, 2:20 a.m. |
| PD | Predicate disambiguation | batch_69fd47d35da081908bec8901018d186c |
completed | May 8, 2026, 2:17 a.m. |
| PDg | Predicate description generation | batch_69fd485e0c20819099756b4fe39ac326 |
completed | May 8, 2026, 2:20 a.m. |
Created at: May 3, 2026, 4:32 p.m.