Triple

T2258581
Position Surface form Disambiguated ID Type / Status
Subject Uncle Tom E49783 entity
Predicate hasChild P369 FINISHED
Object 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.
 E254735 NE FINISHED

How this triple was built (4 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: Mose | Statement: [Uncle Tom, hasChild, Mose]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mose
Context triple: [Uncle Tom, hasChild, Mose]
  • A. Moses
    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. Yoshua
    Yoshua is a male given name most notably borne by Yoshua Bengio, a pioneering Canadian computer scientist and deep learning researcher.
  • C. 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.
  • D. Joshua
    Joshua is a book of the Hebrew Bible and Christian Old Testament that narrates the Israelite conquest and settlement of Canaan under the leadership of Joshua.
  • E. Joshua
    Joshua is a masculine given name of Hebrew origin, commonly used in English-speaking countries.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Mose
Triple: [Uncle Tom, hasChild, Mose]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mose
Target entity description: 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.
  • A. Moses
    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. Yoshua
    Yoshua is a male given name most notably borne by Yoshua Bengio, a pioneering Canadian computer scientist and deep learning researcher.
  • C. 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.
  • D. Joshua
    Joshua is a book of the Hebrew Bible and Christian Old Testament that narrates the Israelite conquest and settlement of Canaan under the leadership of Joshua.
  • E. Joshua
    Joshua is a masculine given name of Hebrew origin, commonly used in English-speaking countries.
  • F. None of above. chosen

Provenance (5 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_69a88aaa9250819095e127d0d77e8a32 completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc15ad06c8190b6d0babc17015787 completed March 7, 2026, 6:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae89477bb481908ce66fac62181f1f completed March 9, 2026, 8:48 a.m.
NEDg Description generation batch_69ae8a1abe708190806a2525377084c2 completed March 9, 2026, 8:51 a.m.
NED2 Entity disambiguation (via description) batch_69ae8a7726dc8190a18f7f1e1609253a completed March 9, 2026, 8:53 a.m.
Created at: March 4, 2026, 7:48 p.m.