Triple

T29677735
Position Surface form Disambiguated ID Type / Status
Subject Chippi Chippi E750861 entity
Predicate artist P184 FINISHED
Object Khaby Lame
Khaby Lame is a Senegalese-born Italian social media personality and comedian best known for his viral TikTok videos silently mocking overly complicated life-hack clips.
E1879012 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: Khaby Lame | Statement: [Chippi Chippi, artist, Khaby Lame]
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: Khaby Lame
Triple: [Chippi Chippi, artist, Khaby Lame]
Generated description
Khaby Lame is a Senegalese-born Italian social media personality and comedian best known for his viral TikTok videos silently mocking overly complicated life-hack clips.

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_69f0d624d7b08190ba237d226f78d0d9 completed April 28, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f6725e8c8c8190baf3a148eb6db098 completed May 2, 2026, 9:53 p.m.
NED1 Entity disambiguation (via context triple) batch_6a267ec1dfbc8190a01b937a3daa987a completed June 8, 2026, 8:35 a.m.
NEDg Description generation batch_6a2682e65ae08190a4d7e0ba5b6cf7f1 completed June 8, 2026, 8:52 a.m.
NED2 Entity disambiguation (via description) batch_6a2687743cfc81909c3a7679bfb29c35 completed June 8, 2026, 9:12 a.m.
Created at: April 28, 2026, 7:08 p.m.