Triple

T25870235
Position Surface form Disambiguated ID Type / Status
Subject Geraldine Jewsbury E651732 entity
Predicate notableWork P4 FINISHED
Object The Half-Sisters
The Half-Sisters is an 1848 social-problem novel by Geraldine Jewsbury that explores the contrasting lives and limited choices of women in Victorian society.
 E1700606 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: The Half-Sisters | Statement: [Geraldine Jewsbury, notableWork, The Half-Sisters]
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: The Half-Sisters
Triple: [Geraldine Jewsbury, notableWork, The Half-Sisters]
Generated description
The Half-Sisters is an 1848 social-problem novel by Geraldine Jewsbury that explores the contrasting lives and limited choices of women in Victorian society.

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_69e7ab3ad9d88190841ddcb93ab02e96 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f602db41d08190b3c1b0b7d904b4bc completed May 2, 2026, 1:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10ecb22dec8190bbc3eff54c86d743 completed May 22, 2026, 11:54 p.m.
NEDg Description generation batch_6a10edc67f448190b6f8da9b63fd6759 completed May 22, 2026, 11:59 p.m.
NED2 Entity disambiguation (via description) batch_6a10ef3e35188190806530f76d78e331 completed May 23, 2026, 12:05 a.m.
Created at: April 22, 2026, 8:11 a.m.