Triple

T14568642
Position Surface form Disambiguated ID Type / Status
Subject Maisie Williams E341853 entity
Predicate appearedIn P795 FINISHED
Object Cyberbully E1106805 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: Cyberbully | Statement: [Maisie Williams, appearedIn, Cyberbully]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cyberbully
Context triple: [Maisie Williams, appearedIn, Cyberbully]
  • A. Cyberbully chosen
    Cyberbully is a 2011 made-for-TV teen drama film that explores the emotional and social consequences of online harassment.
  • B. Cyber Sex
    "Cyber Sex" is a playful, sexually charged pop song by Doja Cat that blends flirtatious lyrics with themes of online intimacy and digital-age romance.
  • C. Cyber-Shades
    Cyber-Shades are a variant of the Cybermen in Doctor Who, characterized by their bestial, hound-like form used for tracking and capturing victims.
  • D. Cyber-King
    The Cyber-King is a colossal, weaponized Cyberman war machine and mobile fortress featured in Doctor Who, serving as a devastating manifestation of Cyberman power.
  • E. Cyber Project
    Cyber Project is a Belfer Center initiative focused on research, policy analysis, and strategy related to cybersecurity and cyber conflict in international affairs.
  • 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_69d822dcc6248190bed689984bceb0e2 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb38d89fc819086709fd3607b835f completed April 14, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd94b4013881908fddb8b3cf8494de completed May 8, 2026, 7:45 a.m.
Created at: April 10, 2026, 1:23 a.m.