Triple
T20732277
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doo Wop motel district |
E509599
|
entity |
| Predicate | hasMediaGenre |
P124610
|
FINISHED |
| Object | retro Americana |
—
|
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: retro Americana | Statement: [Doo Wop motel district, hasMediaGenre, retro Americana]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMediaGenre Context triple: [Doo Wop motel district, hasMediaGenre, retro Americana]
-
A.
hasGenreFeature
Indicates that something possesses a characteristic, element, or trait associated with a particular genre.
-
B.
hasGenreAsSetting
Indicates that a work’s setting is characterized by, or takes place within, a particular genre.
-
C.
hasUseGenre
Indicates that something (such as a work, product, or item) is associated with or categorized under a particular genre for its use or purpose.
-
D.
hasTargetGenreCategory
Indicates that something is associated with or classified under a specific target genre category.
-
E.
hasGenreRelation
chosen
Indicates that there is an association between an entity and a specific genre, specifying the type or category it belongs to.
- 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_69e0b4c589c08190834fb5d86d0efa2b |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c1ee49a48190876fa05eb291e54e |
completed | April 21, 2026, 12:16 a.m. |
| PD | Predicate disambiguation | batch_69e5c04b31248190b9b9d91b5cb854e3 |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 12:31 p.m.