Triple

T34653538
Position Surface form Disambiguated ID Type / Status
Subject The Winning of Barbara Worth E889908 entity
Predicate hasCharacter P2308 FINISHED
Object Barbara Worth
Barbara Worth is the fictional heroine of Harold Bell Wright’s novel "The Winning of Barbara Worth," known for her courage, loyalty, and central role in a Western tale of love and land reclamation in the American desert.
E2107111 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: Barbara Worth | Statement: [The Winning of Barbara Worth, hasCharacter, Barbara Worth]
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: Barbara Worth
Triple: [The Winning of Barbara Worth, hasCharacter, Barbara Worth]
Generated description
Barbara Worth is the fictional heroine of Harold Bell Wright’s novel "The Winning of Barbara Worth," known for her courage, loyalty, and central role in a Western tale of love and land reclamation in the American desert.

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_69f349d906bc8190b2efd9eff237d94b completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f722c6859c8190a3e85fce0e8a342b completed May 3, 2026, 10:26 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3752e7164081908646b6c2d5072ca7 completed June 21, 2026, 2:56 a.m.
NEDg Description generation batch_6a3753626a508190921b016c67753769 completed June 21, 2026, 2:58 a.m.
NED2 Entity disambiguation (via description) batch_6a3753e7179481909051e7b378cbcfbc completed June 21, 2026, 3 a.m.
Created at: May 1, 2026, 2:04 a.m.