Triple

T16148121
Position Surface form Disambiguated ID Type / Status
Subject Why Women Kill E391838 entity
Predicate distributor P1951 FINISHED
Object Paramount+ E59331 NE 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: Paramount+ | Statement: [Why Women Kill, distributor, Paramount+]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paramount+
Context triple: [Why Women Kill, distributor, Paramount+]
  • A. Paramount+ chosen
    Paramount+ is a subscription-based streaming service from Paramount Global that offers live sports, original series, and a wide range of on-demand TV shows and movies.
  • B. Paramount Streaming
    Paramount Streaming is the division of Paramount Global that oversees the company’s portfolio of streaming services, including platforms like Paramount+.
  • C. 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.
  • D. Disney+
    Disney+ is a subscription-based streaming service from The Walt Disney Company that offers movies and TV shows from Disney, Pixar, Marvel, Star Wars, National Geographic, and more.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d87f1c65e48190aa2b4c472e9bafc4 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e21d9551e081908391061b092ff31b completed April 17, 2026, 11:46 a.m.
NED1 Entity disambiguation (via context triple) batch_6a000ec7cc0881909685923113eaba25 completed May 10, 2026, 4:51 a.m.
Created at: April 10, 2026, 5:01 a.m.