Triple

T4195028
Position Surface form Disambiguated ID Type / Status
Subject Nathan Phillips E89128 entity
Predicate givenName P17 FINISHED
Object Nathan E118389 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 Phillips, givenName, Nathan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nathan
Context triple: [Nathan Phillips, givenName, Nathan]
  • A. Nathan chosen
    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
    Nathan is the given first name of the American writer and poet Jean Toomer, known for his modernist work "Cane."
  • D. 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.
  • E. Nate
    Nate is a central fictional character in Margaret Atwood’s novel "Life Before Man," around whom much of the story’s emotional and relational tension revolves.
  • 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_69aed9569a4481908b6c1fcec2a11e21 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af034406348190a56c21b5c08a6828 completed March 9, 2026, 5:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69b58a0d7fa88190a2c830e298542068 completed March 14, 2026, 4:17 p.m.
Created at: March 9, 2026, 3:46 p.m.