Triple

T36028239
Position Surface form Disambiguated ID Type / Status
Subject Make Something Up: Stories You Can’t Unread E1042189 entity
Predicate notableStory P7331 FINISHED
Object "Loser"
"Loser" is a darkly comic short story from the collection *Make Something Up: Stories You Can’t Unread* by Chuck Palahniuk, exploring themes of failure, identity, and the grotesque absurdities of modern life.
E2164296 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: "Loser" | Statement: [Make Something Up: Stories You Can’t Unread, notableStory, "Loser"]
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: "Loser"
Triple: [Make Something Up: Stories You Can’t Unread, notableStory, "Loser"]
Generated description
"Loser" is a darkly comic short story from the collection *Make Something Up: Stories You Can’t Unread* by Chuck Palahniuk, exploring themes of failure, identity, and the grotesque absurdities of modern life.

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_69f76e2c568881909e1e21f85252b0f0 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7ace807f88190a80a8b93c03ec36a completed May 3, 2026, 8:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38c005d5e08190908f13b44475161e completed June 22, 2026, 4:54 a.m.
NEDg Description generation batch_6a38c089e8908190808360aad00f1c35 completed June 22, 2026, 4:56 a.m.
NED2 Entity disambiguation (via description) batch_6a38c0f110348190b121e0a0b38aee30 completed June 22, 2026, 4:58 a.m.
Created at: May 3, 2026, 4:07 p.m.