Triple

T27908804
Position Surface form Disambiguated ID Type / Status
Subject The Sisters E705864 entity
Predicate authorOfSourceWork P2353 FINISHED
Object Myron Brinig
Myron Brinig was an American novelist of the early 20th century known for his socially conscious fiction, often drawing on his Jewish and immigrant background in the American West.
E1832338 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: Myron Brinig | Statement: [The Sisters, authorOfSourceWork, Myron Brinig]
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: Myron Brinig
Triple: [The Sisters, authorOfSourceWork, Myron Brinig]
Generated description
Myron Brinig was an American novelist of the early 20th century known for his socially conscious fiction, often drawing on his Jewish and immigrant background in the American West.

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_69ef96b5aad08190be36a277c31e7004 completed April 27, 2026, 5:02 p.m.
NER Named-entity recognition batch_69f63a2394f881908f4ee8edf77f6c0c completed May 2, 2026, 5:53 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24a2288e6481908e2c19ef59f1bcb5 completed June 6, 2026, 10:41 p.m.
NEDg Description generation batch_6a24a62011a4819082824ee1642d9b23 completed June 6, 2026, 10:58 p.m.
NED2 Entity disambiguation (via description) batch_6a24a6c78e5c81908bba8b3b76a05c5e completed June 6, 2026, 11:01 p.m.
Created at: April 27, 2026, 6:48 p.m.