Triple

T35095023
Position Surface form Disambiguated ID Type / Status
Subject Mr. Brooke E1012843 entity
Predicate hasFullName P16 FINISHED
Object Edward Casaubon Brooke
Edward Casaubon Brooke is the full name of Mr. Brooke, a character in George Eliot’s novel "Middlemarch."
E2125999 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: Edward Casaubon Brooke | Statement: [Mr. Brooke, hasFullName, Edward Casaubon Brooke]
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: Edward Casaubon Brooke
Triple: [Mr. Brooke, hasFullName, Edward Casaubon Brooke]
Generated description
Edward Casaubon Brooke is the full name of Mr. Brooke, a character in George Eliot’s novel "Middlemarch."

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_69f76dd432ec8190969bc32acfc152b1 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78be4531081909bad0aca0f94390a completed May 3, 2026, 5:54 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37cfef35bc81909f8ddb28e1704244 completed June 21, 2026, 11:50 a.m.
NEDg Description generation batch_6a37d09160108190adcf3b1a85a0e8a2 completed June 21, 2026, 11:52 a.m.
NED2 Entity disambiguation (via description) batch_6a37d1d5dad081908a0f25b28428977b completed June 21, 2026, 11:58 a.m.
Created at: May 3, 2026, 4:01 p.m.