Triple

T35637120
Position Surface form Disambiguated ID Type / Status
Subject Colin’s Crest Award E1029750 entity
Predicate firstWinner P11366 FINISHED
Object Khalid Al Qassimi
Khalid Al Qassimi is an Emirati rally driver known for competing in the World Rally Championship and for being the inaugural recipient of the Colin’s Crest Award.
E2150453 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: Khalid Al Qassimi | Statement: [Colin’s Crest Award, firstWinner, Khalid Al Qassimi]
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: Khalid Al Qassimi
Triple: [Colin’s Crest Award, firstWinner, Khalid Al Qassimi]
Generated description
Khalid Al Qassimi is an Emirati rally driver known for competing in the World Rally Championship and for being the inaugural recipient of the Colin’s Crest Award.

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_69f76e087bdc8190a4794bf9c0bd7634 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f79f1d7bfc8190afc36fdfd4ea0b1c completed May 3, 2026, 7:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a386852ce148190b06ff24a2275ae01 completed June 21, 2026, 10:40 p.m.
NEDg Description generation batch_6a386957440c8190bd915a724bbb08ac completed June 21, 2026, 10:44 p.m.
NED2 Entity disambiguation (via description) batch_6a386d862ec88190b40655d39c07c623 completed June 21, 2026, 11:02 p.m.
Created at: May 3, 2026, 4:05 p.m.