Triple

T13236077
Position Surface form Disambiguated ID Type / Status
Subject Send Me No Flowers E315149 entity
Predicate starring P1507 FINISHED
Object Patricia Barry E1082130 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: Patricia Barry | Statement: [Send Me No Flowers, starring, Patricia Barry]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Patricia Barry
Context triple: [Send Me No Flowers, starring, Patricia Barry]
  • A. Patricia Barry chosen
    Patricia Barry was an American film, television, and stage actress known for her prolific character roles from the 1940s through the 1990s.
  • B. Patricia Lynch
    Patricia Lynch was an Irish author best known for her children's books that often blended fantasy with Irish rural life and folklore.
  • C. Patricia O’Callaghan
    Patricia O’Callaghan is a Canadian soprano and cabaret-style singer known for her interpretations of Leonard Cohen’s songs and eclectic repertoire spanning classical, pop, and chanson.
  • D. Patricia Laffan
    Patricia Laffan was a British actress best known for her roles in mid-20th-century films, including notable performances in historical epics and science fiction cinema.
  • E. Patricia Breslin
    Patricia Breslin was an American actress known for her roles in 1950s–60s film and television, including appearances on shows like "The Twilight Zone" and "Peyton Place."
  • 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_69d806affc688190a25b6ccc588e9c72 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98d56da008190af55da3a9e7ffd4d completed April 10, 2026, 11:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69fde15abe6c8190a6212861bbce790e completed May 8, 2026, 1:12 p.m.
Created at: April 9, 2026, 9:22 p.m.