Triple

T11450373
Position Surface form Disambiguated ID Type / Status
Subject Moses Mendel Dessau E271377 entity
Predicate givenName P17 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: [Moses Mendel Dessau, givenName, Moses]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Moses
Context triple: [Moses Mendel Dessau, givenName, 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. Mūsa
    Mūsa is a river in Latvia that serves as one of the main tributaries forming the larger Lielupe River.
  • E. Moses Pray
    Moses Pray is a charmingly roguish Bible salesman and con man who becomes the reluctant guardian and partner-in-crime of a young girl in the film and novel "Paper Moon."
  • 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_69d6aadff8888190a13f253f0d460874 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d81c6e496c8190b0a1919c29d4ee60 completed April 9, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5d3470e208190aef43936bac2e4e9 completed April 20, 2026, 7:18 a.m.
Created at: April 8, 2026, 9:35 p.m.