Triple
T20383582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dames |
E497900
|
entity |
| Predicate | hasFilmSequence |
P77503
|
FINISHED |
| Object | I Only Have Eyes for You Busby Berkeley number |
—
|
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: I Only Have Eyes for You Busby Berkeley number | Statement: [Dames, hasFilmSequence, I Only Have Eyes for You Busby Berkeley number]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFilmSequence Context triple: [Dames, hasFilmSequence, I Only Have Eyes for You Busby Berkeley number]
-
A.
sequenceInFilm
chosen
Indicates that one entity is a specific sequence or segment that appears within the narrative or structure of a particular film.
-
B.
hasLiveActionFilm
Indicates that a subject has a corresponding live-action film adaptation or representation.
-
C.
hasShortFilmSeries
Indicates that an entity is associated with or includes a series of short films.
-
D.
hasInteractiveFilm
Indicates that an entity is associated with, offers, or features an interactive film experience.
-
E.
hasFilmStyle
Indicates that a film exhibits or is characterized by a particular cinematic style or aesthetic approach.
- 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_69e0b4a5b7908190a972e4e7e698ae94 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e678b2ceec819091ad5205ee9b2174 |
completed | April 20, 2026, 7:04 p.m. |
| PD | Predicate disambiguation | batch_69e57648be3c81908256838228cabf5c |
completed | April 20, 2026, 12:41 a.m. |
Created at: April 16, 2026, 11:27 a.m.