Triple

T16429549
Position Surface form Disambiguated ID Type / Status
Subject Miss Kittin E399035 entity
Predicate associatedAct P37 FINISHED
Object The Hacker E1213370 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: The Hacker | Statement: [Miss Kittin, associatedAct, The Hacker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Hacker
Context triple: [Miss Kittin, associatedAct, The Hacker]
  • A. The Hacker
    The Hacker is a villainous character portrayed by Christopher Lloyd in the educational animated television series "Cyberchase."
  • B. The Hacker chosen
    The Hacker is a French electronic music producer and DJ known for his influential work in electroclash and techno, often in collaboration with Miss Kittin.
  • C. The Hacker’s Choice
    The Hacker’s Choice is a well-known security research and hacking collective recognized for creating influential penetration-testing tools and publishing information on network and system vulnerabilities.
  • D. Hackers
    Hackers is a 1995 cult classic cyberpunk film about teenage computer prodigies who uncover a corporate conspiracy while navigating early internet culture.
  • E. Hacking River
    Hacking River is a waterway in New South Wales, Australia, flowing through the Royal National Park and serving as a popular spot for recreation and nature activities.
  • 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_69d87f2b9024819085c20e52de95d583 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e328fd49708190abb5065fa430eff1 completed April 18, 2026, 6:47 a.m.
NED1 Entity disambiguation (via context triple) batch_6a004f477674819093bcf9f0df43ebf9 completed May 10, 2026, 9:26 a.m.
Created at: April 10, 2026, 5:09 a.m.