Triple

T23737850
Position Surface form Disambiguated ID Type / Status
Subject Babbage family E586584 entity
Predicate hasMember P10 FINISHED
Object Henry Prevost Babbage
Henry Prevost Babbage was a British engineer and the youngest son of computing pioneer Charles Babbage, known for helping to preserve and promote his father's work on early mechanical computers.
 E1627124 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: Henry Prevost Babbage | Statement: [Babbage family, hasMember, Henry Prevost Babbage]
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: Henry Prevost Babbage
Triple: [Babbage family, hasMember, Henry Prevost Babbage]
Generated description
Henry Prevost Babbage was a British engineer and the youngest son of computing pioneer Charles Babbage, known for helping to preserve and promote his father's work on early mechanical computers.

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_69e24907dc9c8190be074c9c96a0ec2d completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1bad356c88190ae29ce403145ee73 completed April 29, 2026, 8:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fc98f70288190bc2b3896d4642f30 completed May 22, 2026, 3:12 a.m.
NEDg Description generation batch_6a0fcb41ec208190ab3fb4e8b52c8c81 completed May 22, 2026, 3:19 a.m.
NED2 Entity disambiguation (via description) batch_6a0fcbb4883c81909bb9f02361c69fe7 completed May 22, 2026, 3:21 a.m.
Created at: April 17, 2026, 7:11 p.m.