Triple

T12817009
Position Surface form Disambiguated ID Type / Status
Subject William C. Thompson E306427 entity
Predicate workedOn P3 FINISHED
Object Glen or Glenda E500240 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: Glen or Glenda | Statement: [William C. Thompson, workedOn, Glen or Glenda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Glen or Glenda
Context triple: [William C. Thompson, workedOn, Glen or Glenda]
  • A. Glen or Glenda chosen
    Glen or Glenda is a 1953 low-budget cult film by Ed Wood that explores cross-dressing and gender identity through a highly unconventional, semi-autobiographical narrative.
  • B. Glenda
    Glenda is a character from the horror-comedy film "Seed of Chucky," known as the gender-fluid child of the killer dolls Chucky and Tiffany.
  • C. Glenna
    Glenna is a feminine given name of Irish origin, often interpreted to mean "valley" or "from the glen."
  • D. Glenna
    Glenna is a fictional character distinguished by her prominent horns, often depicted as a horned or demonic figure in her narrative setting.
  • E. Gladys
    Gladys is a feminine given name of English origin that was especially popular in the late 19th and early 20th centuries.
  • 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_69d7bdf46c448190b1faa55aaacb6317 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96e9d00088190ac0f5d60e1de7a7c completed April 10, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69f68ecee33c8190a6bf045731bb9326 completed May 2, 2026, 11:54 p.m.
Created at: April 9, 2026, 5:31 p.m.