Triple

T31393249
Position Surface form Disambiguated ID Type / Status
Subject Boom Chicago E800792 entity
Predicate foundedBy P104 FINISHED
Object Pep Rosenfeld
Pep Rosenfeld is an American comedian, writer, and co-founder of Amsterdam-based improv and sketch comedy theater Boom Chicago, known for his political satire and corporate event hosting.
E2017505 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: Pep Rosenfeld | Statement: [Boom Chicago, foundedBy, Pep Rosenfeld]
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: Pep Rosenfeld
Triple: [Boom Chicago, foundedBy, Pep Rosenfeld]
Generated description
Pep Rosenfeld is an American comedian, writer, and co-founder of Amsterdam-based improv and sketch comedy theater Boom Chicago, known for his political satire and corporate event hosting.

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_69f224e9d7048190b0cc20f9071bd3e4 completed April 29, 2026, 3:34 p.m.
NER Named-entity recognition batch_69f6a02dfbf08190b8f656135262da0d completed May 3, 2026, 1:09 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34927dc0dc8190b736bee9edac7567 completed June 19, 2026, 12:51 a.m.
NEDg Description generation batch_6a3493a36e808190bbbfe3ad8dd86e7a completed June 19, 2026, 12:56 a.m.
NED2 Entity disambiguation (via description) batch_6a34947b6c5c8190beb4bdce0fe9e238 completed June 19, 2026, 12:59 a.m.
Created at: April 29, 2026, 9:19 p.m.