Triple

T27621979
Position Surface form Disambiguated ID Type / Status
Subject Sir Basil Henriques E700602 entity
Predicate name P16 FINISHED
Object Basil Lucas Quixano Henriques
Basil Lucas Quixano Henriques was a British Jewish social worker and philanthropist known for his pioneering work with youth and impoverished communities in London’s East End in the early 20th century.
E1782028 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: Basil Lucas Quixano Henriques | Statement: [Sir Basil Henriques, name, Basil Lucas Quixano Henriques]
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: Basil Lucas Quixano Henriques
Triple: [Sir Basil Henriques, name, Basil Lucas Quixano Henriques]
Generated description
Basil Lucas Quixano Henriques was a British Jewish social worker and philanthropist known for his pioneering work with youth and impoverished communities in London’s East End in the early 20th century.

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_69ef6a4f1d9c8190b0705acda054368d completed April 27, 2026, 1:53 p.m.
NER Named-entity recognition batch_69f630dc90708190a1f81c7fb6562a75 completed May 2, 2026, 5:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12d0f557f88190a4a3399950eb5f8b completed May 24, 2026, 10:20 a.m.
NEDg Description generation batch_6a12d1a671948190add200d3ab2db641 completed May 24, 2026, 10:23 a.m.
NED2 Entity disambiguation (via description) batch_6a12d23dc1b48190aa7f52797b82db62 completed May 24, 2026, 10:26 a.m.
Created at: April 27, 2026, 2:15 p.m.