Triple

T5708043
Position Surface form Disambiguated ID Type / Status
Subject Nathan Bedford Forrest E125833 entity
Predicate givenName P17 FINISHED
Object Nathan E441826 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: Nathan | Statement: [Nathan Bedford Forrest, givenName, Nathan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nathan
Context triple: [Nathan Bedford Forrest, givenName, Nathan]
  • A. Nathan
    Nathan is a prophet in the Hebrew Bible known for advising King David and courageously confronting him over his sin with Bathsheba.
  • B. Nathan
    Nathan is the central character of Gotthold Ephraim Lessing’s play "Nathan the Wise," portrayed as a wise and compassionate Jewish merchant who advocates religious tolerance and humanism.
  • C. Nathan chosen
    Nathan is a common given name used in various cultures, often derived from Hebrew meaning "he gave" or "gift."
  • D. Nathan
    Nathan is the given first name of the American writer and poet Jean Toomer, known for his modernist work "Cane."
  • E. Nate
    Nate is the Allied reporting name for the Nakajima Ki-27, a Japanese single-engine fighter aircraft used extensively by the Imperial Japanese Army Air Service in the late 1930s and early World War II.
  • 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_69c0082d6fe48190b777fb383769e5c8 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c024892fd88190a91133fc88365410 completed March 22, 2026, 5:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c05a6c17608190a9a808c2c77d937c completed March 22, 2026, 9:09 p.m.
Created at: March 22, 2026, 3:45 p.m.