Triple
T33985862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pauline at the Beach |
E871406
|
entity |
| Predicate | posterCaptionLanguage |
P83064
|
FINISHED |
| Object | French |
—
|
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: French | Statement: [Pauline at the Beach, posterCaptionLanguage, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: posterCaptionLanguage Context triple: [Pauline at the Beach, posterCaptionLanguage, French]
-
A.
filmPosterCaptionLanguage
chosen
Indicates the language in which the caption or text on a film’s poster is written.
-
B.
caption
Indicates that a piece of text serves as a descriptive label or explanation for an associated image, video, or other media content.
-
C.
typicalCaptionStyle
Indicates the usual or characteristic way in which captions are written or presented for a given entity or context.
-
D.
mediaLabel
Indicates that a media item is associated with a specific label or tag that characterizes or categorizes it.
-
E.
mapCaption
Indicates that the value is a textual caption or label describing the associated map.
- 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_69f3499e964c8190b674b03f6f791b4b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7064e906881909c3186c646145d34 |
completed | May 3, 2026, 8:24 a.m. |
| PD | Predicate disambiguation | batch_69f70100ec1c8190a6b97f50e88891f2 |
completed | May 3, 2026, 8:02 a.m. |
Created at: May 1, 2026, 1:50 a.m.