Triple

T24861128
Position Surface form Disambiguated ID Type / Status
Subject Chuck Klosterman E622154 entity
Predicate notableWork P4 FINISHED
Object I Wear the Black Hat
I Wear the Black Hat is a non-fiction essay collection by cultural critic Chuck Klosterman that explores the nature of villainy in pop culture, history, and everyday life with his characteristic blend of humor and philosophical reflection.
E1651076 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: I Wear the Black Hat | Statement: [Chuck Klosterman, notableWork, I Wear the Black Hat]
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: I Wear the Black Hat
Triple: [Chuck Klosterman, notableWork, I Wear the Black Hat]
Generated description
I Wear the Black Hat is a non-fiction essay collection by cultural critic Chuck Klosterman that explores the nature of villainy in pop culture, history, and everyday life with his characteristic blend of humor and philosophical reflection.

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_69e2fac350d08190b3affde1b451a8c5 completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f422ecd4088190bf1905b887fef10f completed May 1, 2026, 3:50 a.m.
NED1 Entity disambiguation (via context triple) batch_6a101c5950908190a1425f40c1eff647 completed May 22, 2026, 9:05 a.m.
NEDg Description generation batch_6a1024ac6320819099045f28aea135cf completed May 22, 2026, 9:41 a.m.
NED2 Entity disambiguation (via description) batch_6a102586c1288190bf8eeb513537b189 completed May 22, 2026, 9:44 a.m.
Created at: April 18, 2026, 5:22 a.m.