Triple

T35149619
Position Surface form Disambiguated ID Type / Status
Subject Business Leader of the Year (Washingtonian magazine) E1014948 entity
Predicate hasCategory P87 FINISHED
Object American business awards
American business awards are honors presented in the United States that recognize outstanding achievements, leadership, and innovation in the business community.
E2128141 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: American business awards | Statement: [Business Leader of the Year (Washingtonian magazine), hasCategory, American business awards]
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: American business awards
Triple: [Business Leader of the Year (Washingtonian magazine), hasCategory, American business awards]
Generated description
American business awards are honors presented in the United States that recognize outstanding achievements, leadership, and innovation in the business community.

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.