Triple

T21511787
Position Surface form Disambiguated ID Type / Status
Subject Yeshayahu Leibowitz E530742 entity
Predicate givenName P17 FINISHED
Object Yeshayahu NE NERFINISHED

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: Yeshayahu | Statement: [Yeshayahu Leibowitz, givenName, Yeshayahu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yeshayahu
Context triple: [Yeshayahu Leibowitz, givenName, Yeshayahu]
  • A. Isaiah chosen
    Isaiah is a major prophetic book of the Hebrew Bible and Christian Old Testament, traditionally attributed to the prophet Isaiah and known for its themes of judgment, hope, and messianic prophecy.
  • B. Ezekiel
    Ezekiel is a major Hebrew prophet known for his vivid apocalyptic visions and central role in the biblical Book of Ezekiel.
  • C. Prophet Micah
    Prophet Micah is a Hebrew Bible prophet known for condemning social injustice and foretelling both judgment and restoration for Israel and Judah.
  • D. Jeremiah
    Jeremiah is a major Old Testament prophet whose writings, including themes of covenant and judgment, are frequently referenced in the New Testament.
  • E. Jeremiah
    Jeremiah is a central Sudanese refugee character in the 2014 drama film "The Good Lie," which portrays the experiences of the Lost Boys of Sudan resettling in the United States.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c45c81f08190a6b8bbb70a45aae7 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e9ea863b18819080e3ff249b10ec28 completed April 23, 2026, 9:46 a.m.
Created at: April 16, 2026, 6:25 p.m.