Triple
T16253728
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saturn Award for Best Actress |
E394576
|
entity |
| Predicate | isGenreFocused |
P36845
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Saturn Award for Best Actress, isGenreFocused, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isGenreFocused Context triple: [Saturn Award for Best Actress, isGenreFocused, true]
-
A.
hasMainGenre
Indicates that an entity’s primary or most characteristic genre is the specified genre.
-
B.
hasGenreScope
chosen
Indicates that something (such as a work, collection, or classification) is limited to, defined by, or applicable within a particular genre or set of genres.
-
C.
targetGenre
Indicates the genre that something is specifically aimed at, categorized under, or intended to belong to.
-
D.
hasGenreFeature
Indicates that something possesses a characteristic, element, or trait associated with a particular genre.
-
E.
hasGenreAsSetting
Indicates that a work’s setting is characterized by, or takes place within, a particular genre.
- 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_69d87f2171208190951025e526947816 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e24598c9488190a92df7d8b1824724 |
completed | April 17, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69e219f259e88190bf49d8408c04178e |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:04 a.m.