Triple

T36154284
Position Surface form Disambiguated ID Type / Status
Subject Michael Smart E1045680 entity
Predicate appearsIn P795 FINISHED
Object The Accidental
The Accidental is a 2005 novel by Ali Smith that blends dark comedy and experimental narrative techniques to explore the impact of a mysterious stranger on a dysfunctional British family.
E321083 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 Accidental | Statement: [Michael Smart, appearsIn, The Accidental]
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 Accidental
Triple: [Michael Smart, appearsIn, The Accidental]
Generated description
The Accidental is a 2005 novel by Ali Smith that blends dark comedy and experimental narrative techniques to explore the impact of a mysterious stranger on a dysfunctional British family.

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_69f76e38903c8190a52887620f90aabe completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b365288c8190bcb11fcfba028737 completed May 3, 2026, 8:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39f8f52ce08190ace8b657929478ef completed June 23, 2026, 3:09 a.m.
NEDg Description generation batch_6a39fbbcb73481908c4346df2900a03a completed June 23, 2026, 3:21 a.m.
NED2 Entity disambiguation (via description) batch_6a39fc7cd3288190a17acf9a240987c7 completed June 23, 2026, 3:24 a.m.
Created at: May 3, 2026, 4:08 p.m.