Triple

T4293052
Position Surface form Disambiguated ID Type / Status
Subject Anthony Hamilton E99640 entity
Predicate notableWork P4 FINISHED
Object Charlene E95375 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: Charlene | Statement: [Anthony Hamilton, notableWork, Charlene]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Charlene
Context triple: [Anthony Hamilton, notableWork, Charlene]
  • A. Charlene chosen
    Charlene is a feminine given name derived from the male name Charles.
  • B. Cherie
    Cherie is the naive yet determined young woman who becomes the romantic focus of the cowboy in the classic stage play and film "Bus Stop."
  • C. Carole
    Carole is a feminine given name of French origin, commonly used in English-speaking countries.
  • D. Charlene Fleming
    Charlene Fleming is a central character in the boxing drama film "The Fighter," portrayed as the tough, outspoken girlfriend of boxer Micky Ward.
  • E. Cinnamon Carter
    Cinnamon Carter is a fictional character, a sophisticated and resourceful female agent on the classic television series "Mission: Impossible."
  • 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_69b3455175088190aa79c6e03b86647e completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35082228081908504e3fd7c4ca1e8 completed March 12, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5c739df2c8190af6f8d9bf36afca8 completed March 14, 2026, 8:38 p.m.
Created at: March 12, 2026, 11:08 p.m.