Triple

T35149576
Position Surface form Disambiguated ID Type / Status
Subject Washingtonian of the Year E1014947 entity
Predicate hasNotableRecipient P108 FINISHED
Object Mark Ein
Mark Ein is a Washington, D.C.-based entrepreneur, investor, and philanthropist known for his leadership in business, sports ownership, and civic initiatives in the region.
E2128136 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: Mark Ein | Statement: [Washingtonian of the Year, hasNotableRecipient, Mark Ein]
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: Mark Ein
Triple: [Washingtonian of the Year, hasNotableRecipient, Mark Ein]
Generated description
Mark Ein is a Washington, D.C.-based entrepreneur, investor, and philanthropist known for his leadership in business, sports ownership, and civic initiatives in the region.

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_69f76dda7c108190a2ffd93eb6c341a7 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78cea708c8190a2702c9825b6b094 completed May 3, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37d9603f44819097cee8972098e96d completed June 21, 2026, 12:30 p.m.
NEDg Description generation batch_6a37dbab7c348190b3887844503a265b completed June 21, 2026, 12:40 p.m.
NED2 Entity disambiguation (via description) batch_6a37dd868bf48190bda804117b168193 completed June 21, 2026, 12:48 p.m.
Created at: May 3, 2026, 4:02 p.m.