Triple

T17201735
Position Surface form Disambiguated ID Type / Status
Subject Sylvia Plachy E417489 entity
Predicate employer P7 FINISHED
Object Fortune E3452 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: Fortune | Statement: [Sylvia Plachy, employer, Fortune]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fortune
Context triple: [Sylvia Plachy, employer, Fortune]
  • A. Fortune chosen
    Fortune is a long-running American business magazine known for its influential rankings such as the Fortune 500 and in-depth coverage of global economics and corporate leadership.
  • B. Fortune
    Fortune is the surname of E. Charlton Fortune, an American painter known for her Impressionist and modernist works, particularly coastal scenes of California.
  • C. Fortune
    Fortune is a small coastal town on the Burin Peninsula of Newfoundland and Labrador, Canada, known as a gateway to the French islands of Saint Pierre and Miquelon.
  • D. Fortune
    "Fortune" is a song by British singer-songwriter Laura Marling from her critically acclaimed album "Song for Our Daughter."
  • E. Fortune
    "Fortune" is a film featuring actor Matthew Salinger, known for his role in the 1990 "Captain America" adaptation.
  • 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_69d886d6ba8c819093215917b3d01689 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42db014b08190b88a5001e9f7811b completed April 19, 2026, 1:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a015fdc13d88190bbf9e6d1272814d2 completed May 11, 2026, 4:49 a.m.
Created at: April 10, 2026, 5:38 a.m.