Triple

T15748371
Position Surface form Disambiguated ID Type / Status
Subject Metta Fuller Victor E381780 entity
Predicate familyName P18 FINISHED
Object Victor
Victor is a surname shared by various notable individuals across fields such as literature, entertainment, and public life.
E1173970 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: [Metta Fuller Victor, familyName, Victor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Victor
Context triple: [Metta Fuller Victor, familyName, Victor]
  • A. Victor
    Victor was a prominent early 20th-century record label known for producing and distributing influential jazz and popular music recordings.
  • B. Victor
    Victor is a character in Gregory Benford’s science fiction novel "Timescape," which explores time communication and ecological catastrophe.
  • C. Victor
    Victor is the NATO reporting name for a class of Soviet nuclear-powered attack submarines developed during the Cold War.
  • D. Victor
    Victor is a supporting character in the romantic film "Letters to Juliet," known as Sophie’s work-obsessed fiancé whose priorities contrast with her search for true love.
  • E. Victor
    Victor is a trusted henchman and enforcer for drug kingpin Gustavo Fring in the television series Breaking Bad.
  • 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: [Metta Fuller Victor, familyName, Victor]
Generated description
Victor is a surname shared by various notable individuals across fields such as literature, entertainment, and public life.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Victor
Target entity description: Victor is a surname shared by various notable individuals across fields such as literature, entertainment, and public life.
  • A. Victor
    Victor was a prominent early 20th-century record label known for producing and distributing influential jazz and popular music recordings.
  • B. Victor
    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 is a character in the play "One for the Road," serving as one of the figures through whom the story’s themes of power and oppression are explored.
  • D. Victor
    Victor is a character in Gregory Benford’s science fiction novel "Timescape," which explores time communication and ecological catastrophe.
  • E. 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.
  • 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_69d86d9e6b44819085d1f6a969ecb74c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e0502fd3608190b42e647b9c2b41a1 completed April 16, 2026, 2:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff8309cba881909579ee5a62b3aa31 completed May 9, 2026, 6:55 p.m.
NEDg Description generation batch_69ff83d929a48190aea75597b864d210 completed May 9, 2026, 6:58 p.m.
NED2 Entity disambiguation (via description) batch_69ff8469354c819080b8cfddb7c66be5 completed May 9, 2026, 7 p.m.
Created at: April 10, 2026, 4:46 a.m.