Triple

T24788869
Position Surface form Disambiguated ID Type / Status
Subject Per Petterson E620193 entity
Predicate notableWork P4 FINISHED
Object Out Stealing Horses
Out Stealing Horses is a contemplative Norwegian novel by Per Petterson that follows an aging man's reflections on a formative summer marked by loss, memory, and quiet emotional upheaval.
 E1652818 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: Out Stealing Horses | Statement: [Per Petterson, notableWork, Out Stealing Horses]
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: Out Stealing Horses
Triple: [Per Petterson, notableWork, Out Stealing Horses]
Generated description
Out Stealing Horses is a contemplative Norwegian novel by Per Petterson that follows an aging man's reflections on a formative summer marked by loss, memory, and quiet emotional upheaval.

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_69e2fabdbe8c8190adbb9434b8636cad completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f41101379c8190b5d84f2362d42c5d completed May 1, 2026, 2:33 a.m.
NED1 Entity disambiguation (via context triple) batch_6a101c27d5a48190816f90c67f38beae completed May 22, 2026, 9:04 a.m.
NEDg Description generation batch_6a1024aba7c88190a2d72c92bf9e5723 completed May 22, 2026, 9:40 a.m.
NED2 Entity disambiguation (via description) batch_6a102561fda081908fc03becd4d997ac completed May 22, 2026, 9:44 a.m.
Created at: April 18, 2026, 4:46 a.m.