Triple

T4459612
Position Surface form Disambiguated ID Type / Status
Subject Dollhouse E98218 entity
Predicate mainCharacter P1183 FINISHED
Object 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.
 E443026 NE FINISHED

How this triple was built (4 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: [Dollhouse, mainCharacter, Victor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Victor
Context triple: [Dollhouse, mainCharacter, Victor]
  • A. Victor
    Victor is a masculine given name of Latin origin meaning "conqueror" or "winner," commonly used in many European and English-speaking countries.
  • B. Víctor
    Víctor is a given name commonly used in Spanish-speaking countries, derived from the Latin name Victor meaning "winner" or "conqueror."
  • C. Viktor
    Viktor is the given name of Viktor Frankl, the Austrian neurologist, psychiatrist, and Holocaust survivor who founded logotherapy and wrote "Man’s Search for Meaning."
  • D. Viktor
    Viktor is a powerful and ancient vampire elder from the "Underworld" film series, portrayed by actor Bill Nighy.
  • E. Jules
    Jules is a given name most famously associated with French poet Jules Laforgue, a key figure in Symbolist and early modernist literature.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Victor
Triple: [Dollhouse, mainCharacter, Victor]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Victor
Target entity description: 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.
  • A. Victor
    Victor is a masculine given name of Latin origin meaning "conqueror" or "winner," commonly used in many European and English-speaking countries.
  • B. Víctor
    Víctor is a given name commonly used in Spanish-speaking countries, derived from the Latin name Victor meaning "winner" or "conqueror."
  • C. Viktor
    Viktor is a powerful and ancient vampire elder from the "Underworld" film series, portrayed by actor Bill Nighy.
  • D. Viktor
    Viktor is the given name of Viktor Frankl, the Austrian neurologist, psychiatrist, and Holocaust survivor who founded logotherapy and wrote "Man’s Search for Meaning."
  • E. Jules
    Jules is a given name most famously associated with French poet Jules Laforgue, a key figure in Symbolist and early modernist literature.
  • F. None of above. chosen

Provenance (5 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_69b3454a7c608190944f5455c8031d73 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3567184f481908a2787e4ac9bb345 completed March 13, 2026, 12:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69b6283811f0819095aa671ac593bd8d completed March 15, 2026, 3:32 a.m.
NEDg Description generation batch_69b629532cac8190b959adc0ef13305a completed March 15, 2026, 3:36 a.m.
NED2 Entity disambiguation (via description) batch_69b62d9c287c8190a305f9d21517f913 completed March 15, 2026, 3:55 a.m.
Created at: March 12, 2026, 11:33 p.m.