Triple

T12960050
Position Surface form Disambiguated ID Type / Status
Subject Louis Lambert E310116 entity
Predicate mainCharacter P1183 FINISHED
Object Louis Lambert E310116 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: Louis Lambert | Statement: [Louis Lambert, mainCharacter, Louis Lambert]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Louis Lambert
Context triple: [Louis Lambert, mainCharacter, Louis Lambert]
  • A. Louis Lambert chosen
    Louis Lambert is a philosophical novel by Honoré de Balzac, included in his larger La Comédie humaine cycle, that explores the life and mystical speculations of a gifted but tormented thinker.
  • B. Leo Lambert
    Leo Lambert was an American cave explorer best known for uncovering and developing the underground waterfall attraction Ruby Falls in Tennessee.
  • C. Bruno Pelletier
    Bruno Pelletier is a Canadian singer and musical theatre actor best known internationally for his role as Gringoire in the hit French musical Notre-Dame de Paris.
  • D. Gabriel Le Duc
    Gabriel Le Duc was a 17th-century French architect best known for his work on the Val-de-Grâce church and complex in Paris.
  • E. George Beranger
    George Beranger was an Australian-born silent film actor and director who appeared in numerous Hollywood productions during the 1910s and 1920s.
  • 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_69d7bdfb57a88190836b743e2825feca completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d97e2e44908190bb8b43fc5c3b8a8a completed April 10, 2026, 10:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6c0f0b4c08190a6cb0a098ca6d67b completed May 3, 2026, 3:28 a.m.
Created at: April 9, 2026, 5:44 p.m.