Triple

T1614555
Position Surface form Disambiguated ID Type / Status
Subject Victor, Prince Napoléon E34685 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: [Victor, Prince Napoléon, givenName, Victor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Victor
Context triple: [Victor, Prince Napoléon, givenName, Victor]
  • A. Victor chosen
    Victor is a masculine given name of Latin origin meaning "conqueror" or "winner," commonly used in many European and English-speaking countries.
  • B. 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."
  • C. Jules
    Jules is a given name most famously associated with French poet Jules Laforgue, a key figure in Symbolist and early modernist literature.
  • D. Vincent
    Vincent is a masculine given name of Latin origin, derived from "Vincentius," meaning "conquering" or "to conquer."
  • E. Dr. Igor
    Dr. Igor is a psychiatrist in Paulo Coelho’s novel "Veronika Decides to Die," known for his controversial experimental approach to treating patients in a mental institution.
  • 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_69a885ffc5ec819091afa325d5f9611c completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a9098f384c81909ef836ee779466e2 completed March 5, 2026, 4:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad51ca2bc48190abb83f4d84782334 completed March 8, 2026, 10:39 a.m.
Created at: March 4, 2026, 7:28 p.m.