Triple

T6967146
Position Surface form Disambiguated ID Type / Status
Subject Alf Garnett E161518 entity
Predicate child P120 FINISHED
Object Rita Garnett E163599 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: Rita Garnett | Statement: [Alf Garnett, child, Rita Garnett]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rita Garnett
Context triple: [Alf Garnett, child, Rita Garnett]
  • A. Rita Garnett chosen
    Rita Garnett is a fictional character from the British television sitcom "Till Death Us Do Part."
  • B. Margalo Gillmore
    Margalo Gillmore was an English-born American stage and film actress known for her sophisticated supporting roles in Broadway productions and classic Hollywood films of the mid-20th century.
  • C. Renée Ballard
    Renée Ballard is a tenacious Los Angeles Police Department detective who stars in Michael Connelly’s contemporary crime novels, often working the night shift while pursuing difficult, politically charged cases.
  • D. Mary Richards
    Mary Richards is the independent, career-focused television news producer portrayed by Mary Tyler Moore on the influential 1970s sitcom "The Mary Tyler Moore Show."
  • E. Rita Taggart
    Rita Taggart is an American actress known for her character roles in film and television since the 1970s.
  • 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_69c68853cff881908439d488924a8283 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6db1373d88190967b42630f8688d6 completed March 27, 2026, 7:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69c76195e69c8190a8f7d9ca223a96e6 completed March 28, 2026, 5:05 a.m.
Created at: March 27, 2026, 2:30 p.m.