Triple

T7081490
Position Surface form Disambiguated ID Type / Status
Subject Joseph Victor Anthony Ruston E164965 entity
Predicate givenName P17 FINISHED
Object Victor E30470 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: Victor | Statement: [Joseph Victor Anthony Ruston, givenName, Victor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Victor
Context triple: [Joseph Victor Anthony Ruston, givenName, Victor]
  • A. Victor
    Victor is a central character in the TV series "Dollhouse," known as one of the programmable "Actives" whose identity and memories are repeatedly altered for various missions.
  • B. Victor chosen
    Victor is a masculine given name of Latin origin meaning "conqueror" or "winner," commonly used in many European and English-speaking countries.
  • C. Victor
    Victor was a prominent early 20th-century record label known for producing and distributing influential jazz and popular music recordings.
  • D. Víctor
    Víctor is a given name commonly used in Spanish-speaking countries, derived from the Latin name Victor meaning "winner" or "conqueror."
  • E. Viktor
    Viktor is a powerful and ancient vampire elder from the "Underworld" film series, portrayed by actor Bill Nighy.
  • 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_69c6887cbc6c8190bdfac42d940f4d8a completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e4f1f5748190b214856bcfc70d81 completed March 27, 2026, 8:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69c79477a79c81909b51175a24d17142 completed March 28, 2026, 8:42 a.m.
Created at: March 27, 2026, 2:40 p.m.