Triple

T15904265
Position Surface form Disambiguated ID Type / Status
Subject Frenzy E385668 entity
Predicate starring P1507 FINISHED
Object Vivien Merchant E311150 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: Vivien Merchant | Statement: [Frenzy, starring, Vivien Merchant]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vivien Merchant
Context triple: [Frenzy, starring, Vivien Merchant]
  • A. Vivien Merchant chosen
    Vivien Merchant was an English stage and film actress known for her intense performances in British drama during the 1960s and 1970s.
  • B. Marie Windsor
    Marie Windsor was an American character actress best known for her tough, sultry roles in film noir and B-movies during the 1940s and 1950s.
  • C. Celia Johnson
    Celia Johnson was a distinguished English actress best known for her nuanced, understated performances in classic British films such as "Brief Encounter."
  • D. Eileen Le Mesurier
    Eileen Le Mesurier was the mother of British journalist and spy Jeremy Wolfenden, connected to mid-20th-century British intellectual and diplomatic circles.
  • 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_69d86da686e4819097cbf3b1fc2d881d completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1563f74d88190a3d92ca0ad46e867 completed April 16, 2026, 9:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a003c4303888190a93830ef534715ae completed May 10, 2026, 8:05 a.m.
Created at: April 10, 2026, 4:52 a.m.