Triple

T14443071
Position Surface form Disambiguated ID Type / Status
Subject The Count of Monte Cristo (1954 film) E358133 entity
Predicate composer P1361 FINISHED
Object Jean Wiener E977750 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: Jean Wiener | Statement: [The Count of Monte Cristo (1954 film), composer, Jean Wiener]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jean Wiener
Context triple: [The Count of Monte Cristo (1954 film), composer, Jean Wiener]
  • A. Jean Wiener chosen
    Jean Wiener was a French composer and pianist known for his film scores and contributions to early 20th-century French popular and classical music.
  • B. John Wieners
    John Wieners was an American poet associated with the Beat and Black Mountain movements, known for his emotionally raw, lyrical explorations of queer identity, desire, and urban life.
  • C. Howard Lilienthal
    Howard Lilienthal is an individual notable enough to be recognized as a namesake or prominent bearer of the surname Lilienthal.
  • D. Jean Peters
    Jean Peters was an American film actress best known for her leading roles in 1940s and 1950s Hollywood adventure and drama films.
  • E. Everett Riskin
    Everett Riskin was an American film producer active during Hollywood’s studio era, known for his work on popular comedies and mystery films.
  • 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_69d8279402a88190821ffa39ae15bccf completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de915d28ec81909e72124e9dd67bfb completed April 14, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd5bdd0f388190870ddd01f66d3e99 completed May 8, 2026, 3:43 a.m.
Created at: April 10, 2026, 1:19 a.m.