Triple

T16254228
Position Surface form Disambiguated ID Type / Status
Subject Deuteronomy 33:23 E394587 entity
Predicate traditionalAuthorship P6838 FINISHED
Object Moses E11297 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: Moses | Statement: [Deuteronomy 33:23, traditionalAuthorship, Moses]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Moses
Context triple: [Deuteronomy 33:23, traditionalAuthorship, Moses]
  • A. Moses chosen
    Moses is a central prophet and leader in the Hebrew Bible, traditionally credited with leading the Israelites out of Egypt and receiving the Ten Commandments from God.
  • B. Moses
    Moses is a narrative poem by Ukrainian writer Ivan Franko that reinterprets the biblical story of the prophet Moses as an allegory for the Ukrainian people's struggle and destiny.
  • C. Mose
    Mose is a minor character in Harriet Beecher Stowe’s novel "Uncle Tom’s Cabin," depicted as one of Uncle Tom’s children within the enslaved family central to the story.
  • D. Moshe
    Moshe is the Hebrew given name of the influential 16th-century Polish rabbi and halachic authority known as the Rema of Kraków (Rabbi Moses Isserles).
  • E. Mūsa
    Mūsa is a river in Latvia that serves as one of the main tributaries forming the larger Lielupe River.
  • 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_69d87f2171208190951025e526947816 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e24598c9488190a92df7d8b1824724 completed April 17, 2026, 2:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0017b1e22c8190bddca67661121c2d completed May 10, 2026, 5:29 a.m.
Created at: April 10, 2026, 5:04 a.m.