Triple
T5741702
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lauren Weisberger |
E126628
|
entity |
| Predicate | The Devil Wears Prada |
P15523
|
FINISHED |
| Object | adaptedIntoFilm |
—
|
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: adaptedIntoFilm | Statement: [Lauren Weisberger, The Devil Wears Prada, adaptedIntoFilm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: The Devil Wears Prada Context triple: [Lauren Weisberger, The Devil Wears Prada, adaptedIntoFilm]
-
A.
מאפיין עונתי
Indicates that something exhibits a seasonal characteristic, pattern, or variation over time.
-
B.
Inside Out Project
Indicates a relationship where an initiative or action turns internal perspectives, stories, or issues outward into public, visible expression or engagement.
-
C.
bride
Indicates that an entity is a woman who is getting married or has just been married in relation to a wedding event or spouse.
-
D.
fareMedia
Indicates that a particular type of ticket, pass, or payment instrument is used as the medium for paying a fare.
-
E.
adaptedWorkOf
chosen
Indicates that one work is derived from, based on, or reinterprets the content of another pre-existing 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_69c0083179548190b384b0bf3c08ca4d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02b52663c8190ab44258468d4296d |
completed | March 22, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69c021ca61688190875bd6107161c284 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:48 p.m.