Triple

T2910643
Position Surface form Disambiguated ID Type / Status
Subject Beauty and the Beast (1987 TV series) E63674 entity
Predicate character P662 FINISHED
Object Vincent E18457 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: Vincent | Statement: [Beauty and the Beast (1987 TV series), character, Vincent]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vincent
Context triple: [Beauty and the Beast (1987 TV series), character, Vincent]
  • A. Vincent chosen
    Vincent is a masculine given name of Latin origin, derived from "Vincentius," meaning "conquering" or "to conquer."
  • B. Vincenzo
    Vincenzo is the Italian given name equivalent to Vincent, commonly used in Italy and among Italian-speaking communities.
  • C. Vincent Gardenia
    Vincent Gardenia was an Italian-American character actor known for his acclaimed supporting roles in films such as "Moonstruck" and "Bang the Drum Slowly," as well as his work on stage and television.
  • D. Victor
    Victor is a masculine given name of Latin origin meaning "conqueror" or "winner," commonly used in many European and English-speaking countries.
  • 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.
  • 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_69ab4c44ab448190b9411324e8a1fc1d completed March 6, 2026, 9:51 p.m.
NER Named-entity recognition batch_69abe0e899808190a348e1e71116d0a5 completed March 7, 2026, 8:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69b0561b8e6c8190be69fd39bdd19cca completed March 10, 2026, 5:34 p.m.
Created at: March 6, 2026, 10:11 p.m.