Triple

T5311066
Position Surface form Disambiguated ID Type / Status
Subject Mad Cows E119027 entity
Predicate hasCastMember P2308 FINISHED
Object Anna Massey E440436 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: Anna Massey | Statement: [Mad Cows, hasCastMember, Anna Massey]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anna Massey
Context triple: [Mad Cows, hasCastMember, Anna Massey]
  • A. Anna Massey chosen
    Anna Massey was an acclaimed English actress known for her nuanced performances in film, television, and theatre, including notable roles in psychological dramas and literary adaptations.
  • B. Edith Lesley
    Edith Lesley was an American educator and founder of the teacher-training institution that evolved into Lesley University in Cambridge, Massachusetts.
  • C. Peggy Ashcroft
    Peggy Ashcroft was a distinguished English stage and film actress renowned for her Shakespearean performances and her long, influential career in British theatre.
  • D. Celia Johnson
    Celia Johnson was a distinguished English actress best known for her nuanced, understated performances in classic British films such as "Brief Encounter."
  • E. Flora Robson
    Flora Robson was a distinguished British actress known for her powerful character roles in both stage and film, often portraying strong, authoritative women.
  • 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_69bd446b57bc8190a513d2e6c40314f3 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd85343ae08190bd9801ea4eac7003 completed March 20, 2026, 5:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf8335f5a48190973622011df4c108 completed March 22, 2026, 5:50 a.m.
Created at: March 20, 2026, 1:53 p.m.