Triple

T6531303
Position Surface form Disambiguated ID Type / Status
Subject The Table Spread E152235 entity
Predicate mentions P831 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: [The Table Spread, mentions, Moses]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Moses
Context triple: [The Table Spread, mentions, 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. 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.
  • C. Mūsa
    Mūsa is a river in Latvia that serves as one of the main tributaries forming the larger Lielupe River.
  • D. 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."
  • E. Moses the Black
    Moses the Black was a 4th-century Ethiopian desert monk and former bandit who became a renowned Christian ascetic and saint among the Desert Fathers.
  • 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_69c688048ec8819093a47f7d332e12ec completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6adbcf820819097ca33a5fc14fd64 completed March 27, 2026, 4:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d52ca9988190addfdae6d7b53a6e completed March 27, 2026, 7:06 p.m.
Created at: March 27, 2026, 1:46 p.m.