Triple

T33949970
Position Surface form Disambiguated ID Type / Status
Subject Kathleen Kent E870411 entity
Predicate notableWork P4 FINISHED
Object The Traitor’s Wife
The Traitor’s Wife is a historical novel by Kathleen Kent that explores the Salem witch trials through the perspective of a woman entangled in the events leading up to the infamous hysteria.
 E1768321 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 Traitor’s Wife | Statement: [Kathleen Kent, notableWork, The Traitor’s Wife]
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 Traitor’s Wife
Triple: [Kathleen Kent, notableWork, The Traitor’s Wife]
Generated description
The Traitor’s Wife is a historical novel by Kathleen Kent that explores the Salem witch trials through the perspective of a woman entangled in the events leading up to the infamous hysteria.

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_69f3499c2d7481909c953a5010227725 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f702771b5c8190a4879314605034c2 completed May 3, 2026, 8:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3689de02ec81908a3779160cc43c65 completed June 20, 2026, 12:38 p.m.
NEDg Description generation batch_6a368a5f070c81909a5d0e8f4ac5ad2e completed June 20, 2026, 12:41 p.m.
NED2 Entity disambiguation (via description) batch_6a368b17fd848190be803db49a0ef089 completed June 20, 2026, 12:44 p.m.
Created at: May 1, 2026, 1:49 a.m.