Triple
T13912146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | C. Y. Lee |
E334523
|
entity |
| Predicate | hasWorkInTheGenre |
P14417
|
FINISHED |
| Object | Asian American fiction |
—
|
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: Asian American fiction | Statement: [C. Y. Lee, hasWorkInTheGenre, Asian American fiction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWorkInTheGenre Context triple: [C. Y. Lee, hasWorkInTheGenre, Asian American fiction]
-
A.
workedOnGenre
chosen
Indicates that an entity (such as a person or organization) has done work related to a particular genre.
-
B.
belongsToWorkGenre
Indicates that a creative work is classified under or associated with a particular genre.
-
C.
hasGenreInPortfolio
Indicates that an entity (such as a creator, label, or catalog) includes a particular genre within its body of work or offerings.
-
D.
hasGenreInRoles
Indicates that an entity participates in roles associated with a particular genre or set of genres.
-
E.
basedOnWorkGenre
Indicates that one entity’s genre classification is derived from or determined by the genre of another work.
- 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_69d81c5eaa9c819083b1ff8689179565 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2723461881908376b5509ee0d530 |
completed | April 14, 2026, 11:38 a.m. |
| PD | Predicate disambiguation | batch_69de059e4ba881908554f72e889719fa |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:16 p.m.