Triple

T16697935
Position Surface form Disambiguated ID Type / Status
Subject Follow Me Quietly E405764 entity
Predicate starring P1507 FINISHED
Object Frank Ferguson E488536 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: Frank Ferguson | Statement: [Follow Me Quietly, starring, Frank Ferguson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frank Ferguson
Context triple: [Follow Me Quietly, starring, Frank Ferguson]
  • A. Frank Ferguson chosen
    Frank Ferguson was an American character actor known for his numerous supporting roles in Western films and television series during the mid-20th century.
  • B. Jay Ferguson
    Jay Ferguson is an American composer and former rock musician best known for writing the theme music for the U.S. television series "The Office."
  • C. Mark Foster
    Mark Foster is an American musician best known as the lead singer and songwriter of the indie pop band Foster the People.
  • D. Keith Fletcher
    Keith Fletcher was an English cricketer and coach best known as a stylish middle-order batsman who captained both Essex and England during a distinguished career in the 1960s–1980s.
  • E. Fredro Starr
    Fredro Starr is an American rapper and actor best known as a member of the hip hop group Onyx and for his roles in film and television during the 1990s and 2000s.
  • 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_69d8838db21081909589220fd71440a4 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3832f550c8190bf7514d4611dec6a completed April 18, 2026, 1:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00919ee61c81909928dd26270e9614 completed May 10, 2026, 2:09 p.m.
Created at: April 10, 2026, 5:19 a.m.