Triple

T28835141
Position Surface form Disambiguated ID Type / Status
Subject Crazy Monkey Presents Straight Outta Benoni E728158 entity
Predicate partOf P40 FINISHED
Object Crazy Monkey franchise
The Crazy Monkey franchise is a South African comedy brand best known for its slapstick, mockumentary-style sketches and films centered on a group of hapless suburban characters.
E1835829 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: Crazy Monkey franchise | Statement: [Crazy Monkey Presents Straight Outta Benoni, partOf, Crazy Monkey franchise]
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: Crazy Monkey franchise
Triple: [Crazy Monkey Presents Straight Outta Benoni, partOf, Crazy Monkey franchise]
Generated description
The Crazy Monkey franchise is a South African comedy brand best known for its slapstick, mockumentary-style sketches and films centered on a group of hapless suburban characters.

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_69f0319dc6088190bbfaa206d40ed74a completed April 28, 2026, 4:03 a.m.
NER Named-entity recognition batch_69f6596cb08c8190908072a531179743 completed May 2, 2026, 8:07 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24bbaeaa1c8190bcab7ce401c74ff8 completed June 7, 2026, 12:30 a.m.
NEDg Description generation batch_6a24c04fe0f48190829c6dd2c0026650 completed June 7, 2026, 12:50 a.m.
NED2 Entity disambiguation (via description) batch_6a24c4255b748190985f57aedda13c1c completed June 7, 2026, 1:06 a.m.
Created at: April 28, 2026, 6:39 a.m.