Triple

T29327482
Position Surface form Disambiguated ID Type / Status
Subject Riverside International Raceway E743690 entity
Predicate notableDriverAssociated P1481 FINISHED
Object Mark Donohue
Mark Donohue was an American racing driver and engineer renowned for his success in sports car, IndyCar, and NASCAR competition, as well as his close association with Team Penske.
E1879245 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 Donohue | Statement: [Riverside International Raceway, notableDriverAssociated, Mark Donohue]
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 Donohue
Triple: [Riverside International Raceway, notableDriverAssociated, Mark Donohue]
Generated description
Mark Donohue was an American racing driver and engineer renowned for his success in sports car, IndyCar, and NASCAR competition, as well as his close association with Team Penske.

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_69f09125f784819080f4e9fce9fe624f completed April 28, 2026, 10:51 a.m.
NER Named-entity recognition batch_69f6689782388190a36b98ec2d60d63f completed May 2, 2026, 9:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a267e95815c81909caf78f41d98811e completed June 8, 2026, 8:34 a.m.
NEDg Description generation batch_6a2682b72dc881909ee96a24b8cd2427 completed June 8, 2026, 8:52 a.m.
NED2 Entity disambiguation (via description) batch_6a2687c32e1c8190a9da1493708e831e completed June 8, 2026, 9:13 a.m.
Created at: April 28, 2026, 1:27 p.m.