Triple

T31208846
Position Surface form Disambiguated ID Type / Status
Subject Black Mirror: San Junipero E795677 entity
Predicate hasEpisodePrecededBy P45886 FINISHED
Object Shut Up and Dance
"Shut Up and Dance" is a tense, techno-paranoia–driven episode of the anthology series Black Mirror that follows a young man blackmailed by mysterious hackers into committing increasingly disturbing acts.
E1952474 NE FINISHED

How this triple was built (3 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: Shut Up and Dance | Statement: [Black Mirror: San Junipero, hasEpisodePrecededBy, Shut Up and Dance]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Shut Up and Dance
Triple: [Black Mirror: San Junipero, hasEpisodePrecededBy, Shut Up and Dance]
Generated description
"Shut Up and Dance" is a tense, techno-paranoia–driven episode of the anthology series Black Mirror that follows a young man blackmailed by mysterious hackers into committing increasingly disturbing acts.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasEpisodePrecededBy
Context triple: [Black Mirror: San Junipero, hasEpisodePrecededBy, Shut Up and Dance]
  • A. hasEpisode
    Indicates that something, typically a series or program, includes a specific episode as one of its constituent parts.
  • B. hasEpisodeAbout
    Indicates that a particular episode (such as of a show, podcast, or series) focuses on, discusses, or is centered around a specified subject or topic.
  • C. hasEpisodeCode
    Indicates that an episode is associated with a specific identifying code or number.
  • D. followsEpisode chosen
    Indicates that one episode occurs directly after another in a sequence or series.
  • E. hasEpisodeStructure
    Indicates that one entity defines or possesses the episodic organization, sequencing, or structural pattern of another (such as a series, season, or narrative work).
  • F. None of above.

Provenance (6 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_69f224d8c6608190b7882466521f62be completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69c25dff481908c9ecd0bfa358a6f completed May 3, 2026, 12:51 a.m.
NED1 Entity disambiguation (via context triple) batch_6a295924d7c08190855eed39454183cb completed June 10, 2026, 12:31 p.m.
NEDg Description generation batch_6a2959d4ecac8190a55af600fc9cc74a completed June 10, 2026, 12:34 p.m.
NED2 Entity disambiguation (via description) batch_6a295cb4623c8190b7d5cf9a072627f7 completed June 10, 2026, 12:46 p.m.
PD Predicate disambiguation batch_69f696673214819094350e1d2648ef34 completed May 3, 2026, 12:27 a.m.
Created at: April 29, 2026, 9:09 p.m.