Triple

T37354911
Position Surface form Disambiguated ID Type / Status
Subject Ty Pennington E927426 entity
Predicate educatedAt P5 FINISHED
Object Art Institute of Atlanta
The Art Institute of Atlanta is a private, for-profit college specializing in design, media arts, fashion, and culinary programs.
E2223570 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: Art Institute of Atlanta | Statement: [Ty Pennington, educatedAt, Art Institute of Atlanta]
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: Art Institute of Atlanta
Triple: [Ty Pennington, educatedAt, Art Institute of Atlanta]
Generated description
The Art Institute of Atlanta is a private, for-profit college specializing in design, media arts, fashion, and culinary programs.

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_69f76eb701788190b40824bc4594d985 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fb5bc3d37c8190bb7d0f9e68f9d8d7 completed May 6, 2026, 3:18 p.m.
NED1 Entity disambiguation (via context triple) batch_6a406ce290bc8190a4e3cd84eee85fd0 completed June 28, 2026, 12:37 a.m.
NEDg Description generation batch_6a406dd62dac8190afef2839157d7d30 completed June 28, 2026, 12:41 a.m.
NED2 Entity disambiguation (via description) batch_6a406e8f3e6c819089d8897547f05ed5 completed June 28, 2026, 12:45 a.m.
Created at: May 3, 2026, 4:16 p.m.