Triple
T6043409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dandy Dan |
E134603
|
entity |
| Predicate | genreOfCharacter |
P68359
|
FINISHED |
| Object | musical gangster |
—
|
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: musical gangster | Statement: [Dandy Dan, genreOfCharacter, musical gangster]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreOfCharacter Context triple: [Dandy Dan, genreOfCharacter, musical gangster]
-
A.
genreRole
Indicates a relationship where an entity holds a specific functional or categorical role within a particular genre.
-
B.
typeOfCharacter
Indicates that one entity is a specific kind or category of character in relation to another entity.
-
C.
genreOfAssociatedPerson
Indicates that a particular genre is associated with a given person, such as an artist, author, or performer.
-
D.
genreOfWorkCharacterIsIn
Indicates the specific genre of the creative work in which a given character appears.
-
E.
genreOfQuotes
Indicates that one entity is the literary, thematic, or stylistic genre to which the other entity’s quotes belong.
- 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_69c00876a69881908088a2626d3b2666 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c056e2b1148190908c4dc43abee266 |
completed | March 22, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69c049eb52a08190ac10fd703735f5aa |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04e8d4a148190bd8f95caae978e1b |
completed | March 22, 2026, 8:18 p.m. |
Created at: March 22, 2026, 4:08 p.m.