Triple

T31098827
Position Surface form Disambiguated ID Type / Status
Subject United States v. Kwame Kilpatrick E792614 entity
Predicate defendant P2238 FINISHED
Object Bobby Ferguson
Bobby Ferguson is a Detroit-based contractor and close associate of former mayor Kwame Kilpatrick who became widely known for his role in a major public corruption and racketeering case involving city contracts.
E1959723 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: Bobby Ferguson | Statement: [United States v. Kwame Kilpatrick, defendant, Bobby Ferguson]
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: Bobby Ferguson
Triple: [United States v. Kwame Kilpatrick, defendant, Bobby Ferguson]
Generated description
Bobby Ferguson is a Detroit-based contractor and close associate of former mayor Kwame Kilpatrick who became widely known for his role in a major public corruption and racketeering case involving city contracts.

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_69f224cf157c81909e2d2bd88c9282c3 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f696aa1ea48190bee5ad7383bc82a2 completed May 3, 2026, 12:28 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2a71f0352c8190ba9e595320b4a32c completed June 11, 2026, 8:29 a.m.
NEDg Description generation batch_6a2a75d68da48190b86388e077acf1e5 completed June 11, 2026, 8:46 a.m.
NED2 Entity disambiguation (via description) batch_6a2abcd99ec48190af20507cac16aae7 completed June 11, 2026, 1:49 p.m.
Created at: April 29, 2026, 9:03 p.m.