Triple

T13710824
Position Surface form Disambiguated ID Type / Status
Subject Glenne Headly E328765 entity
Predicate name P16 FINISHED
Object Glenne Headly E328765 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: Glenne Headly | Statement: [Glenne Headly, name, Glenne Headly]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Glenne Headly
Context triple: [Glenne Headly, name, Glenne Headly]
  • A. Glenne Headly chosen
    Glenne Headly was an American actress known for her versatile film, television, and stage performances, including prominent roles in comedies and dramas from the 1980s onward.
  • B. Laurie Durning
    Laurie Durning is an American filmmaker and costume designer best known for her long-term relationship and later marriage to Pink Floyd co-founder Roger Waters.
  • C. Lynn Collins
    Lynn Collins is an American actress known for her roles in films such as X-Men Origins: Wolverine and John Carter, as well as various television series.
  • D. Melissa Sue Anderson
    Melissa Sue Anderson is an American actress best known for her role as Mary Ingalls on the television series "Little House on the Prairie."
  • E. Alice Patten
    Alice Patten is a British actress best known internationally for her role as an English documentary filmmaker in the acclaimed Indian film "Rang De Basanti."
  • 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_69d80770b9bc81909f70c8c317d53cff completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dd43949e6c8190ae5e4fa119cde33a completed April 13, 2026, 7:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69fbc315ff848190a6c8cbd5b90db7fc completed May 6, 2026, 10:39 p.m.
Created at: April 9, 2026, 9:54 p.m.