Triple

T2480939
Position Surface form Disambiguated ID Type / Status
Subject Frank Farmer E55812 entity
Predicate employedBy P7 FINISHED
Object Rachel Marron E75923 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: Rachel Marron | Statement: [Frank Farmer, employedBy, Rachel Marron]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rachel Marron
Context triple: [Frank Farmer, employedBy, Rachel Marron]
  • A. Rachel Marron chosen
    Rachel Marron is a famous pop singer and actress who becomes the client and love interest of a former Secret Service agent in the romantic thriller film "The Bodyguard."
  • B. Mary Morello
    Mary Morello is an American activist and former schoolteacher best known as the mother of Rage Against the Machine guitarist Tom Morello.
  • C. Emily Dreyfuss
    Emily Dreyfuss is an American journalist and writer known for her work on technology, politics, and digital culture for outlets such as WIRED and the Harvard Shorenstein Center.
  • D. Margo Anderson
    Margo Anderson is best known as a former wife of American country music star Kenny Rogers.
  • E. Marilou York
    Marilou York is an American dental hygienist best known as the longtime wife of actor Mark Hamill.
  • 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_69ab49e670a88190b928e08302381710 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd161bf3c8190834502968180e9cf completed March 7, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69b2248bcb68819095e52fea4cd5692c completed March 12, 2026, 2:27 a.m.
Created at: March 6, 2026, 9:45 p.m.