Triple

T15977782
Position Surface form Disambiguated ID Type / Status
Subject Edward Alderson E387492 entity
Predicate fictionalUniverse P3758 FINISHED
Object Mr. Robot universe E89798 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: Mr. Robot universe | Statement: [Edward Alderson, fictionalUniverse, Mr. Robot universe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mr. Robot universe
Context triple: [Edward Alderson, fictionalUniverse, Mr. Robot universe]
  • A. Mr. Robot chosen
    Mr. Robot is a critically acclaimed psychological thriller television series about a socially anxious hacker drawn into an underground cyber-activist group.
  • B. Whiterose in Mr. Robot
    Whiterose in Mr. Robot is a mysterious and powerful hacker and Chinese government official who leads the Dark Army and serves as one of the series’ primary antagonists.
  • C. Westworld
    Westworld is a 1973 science fiction thriller film about a futuristic amusement park where lifelike robots malfunction and turn deadly.
  • D. Westworld
    Westworld is a science fiction television series that explores artificial intelligence, consciousness, and morality within a technologically advanced Wild West–themed amusement park.
  • E. Halt and Catch Fire
    Halt and Catch Fire is a critically acclaimed drama television series about a group of innovators navigating the early personal computing and internet boom of the 1980s and 1990s.
  • 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_69d86da94ccc819083d187f5dc6a123e completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e157521f6c8190a54023b5ee6fc033 completed April 16, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fff293c2248190993d5d74eaf626bc completed May 10, 2026, 2:50 a.m.
Created at: April 10, 2026, 4:54 a.m.