Triple
T20006808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Behind Her Eyes |
E494480
|
entity |
| Predicate | distributor |
P1951
|
FINISHED |
| Object | Netflix |
—
|
NE NERFINISHED |
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: Netflix | Statement: [Behind Her Eyes, distributor, Netflix]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Netflix Context triple: [Behind Her Eyes, distributor, Netflix]
-
A.
Netflix
chosen
Netflix is a global streaming entertainment company best known for its vast library of films and TV series and its influential original content.
-
B.
Hulu
Hulu is a U.S.-based subscription streaming service offering on-demand access to a wide range of television shows, films, and original content.
-
C.
Amazon Prime Video
Amazon Prime Video is a subscription-based streaming service from Amazon that offers a wide range of movies, TV series, and original content available on-demand across multiple devices.
-
D.
HBO Max
HBO Max is a streaming service from WarnerMedia that offers a wide library of movies, series, and original content from HBO and related brands.
-
E.
Amazon Freevee
Amazon Freevee is a free, ad-supported streaming service from Amazon that offers a mix of movies, TV shows, and original programming.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da626b2d748190886981ea90c8b2ea |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e661a648a88190853ee741edcf6ca2 |
completed | April 20, 2026, 5:25 p.m. |
Created at: April 11, 2026, 3:33 p.m.