Triple

T38504045
Position Surface form Disambiguated ID Type / Status
Subject Our Souls at Night E919913 entity
Predicate featuresCharacter P626 FINISHED
Object Addie Moore
Addie Moore is the widowed, quietly determined woman in Kent Haruf’s novel "Our Souls at Night," who initiates an unconventional companionship with her neighbor to ease their shared loneliness in a small Colorado town.
E2273647 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: Addie Moore | Statement: [Our Souls at Night, featuresCharacter, Addie Moore]
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: Addie Moore
Triple: [Our Souls at Night, featuresCharacter, Addie Moore]
Generated description
Addie Moore is the widowed, quietly determined woman in Kent Haruf’s novel "Our Souls at Night," who initiates an unconventional companionship with her neighbor to ease their shared loneliness in a small Colorado town.

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_69f76e9ddd4481908f8c04439d848f9d completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fcd265675481908e1c199e1e1eae07 completed May 7, 2026, 5:56 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41d65b1de48190b25d60f7d053796a completed June 29, 2026, 2:20 a.m.
NEDg Description generation batch_6a41d9e3540c8190add45c48a8977a1f completed June 29, 2026, 2:35 a.m.
NED2 Entity disambiguation (via description) batch_6a41da4ab17c8190ab53f002ddb814aa completed June 29, 2026, 2:36 a.m.
Created at: May 3, 2026, 4:31 p.m.