Triple

T36075175
Position Surface form Disambiguated ID Type / Status
Subject 1984 Brazilian Grand Prix E1043477 entity
Predicate polePositionDriver P51158 FINISHED
Object Elio de Angelis
Elio de Angelis was an Italian Formula One driver of the late 1970s and early 1980s, best known for his speed, smooth driving style, and victories with the Lotus team.
E2170023 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: Elio de Angelis | Statement: [1984 Brazilian Grand Prix, polePositionDriver, Elio de Angelis]
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: Elio de Angelis
Triple: [1984 Brazilian Grand Prix, polePositionDriver, Elio de Angelis]
Generated description
Elio de Angelis was an Italian Formula One driver of the late 1970s and early 1980s, best known for his speed, smooth driving style, and victories with the Lotus team.

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_69f76e2fd3248190b900d9a492bf5a7a completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b238e3188190a6ae41ea3025bd71 completed May 3, 2026, 8:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38ddf9b75881909559c395ee69a03c completed June 22, 2026, 7:02 a.m.
NEDg Description generation batch_6a38ea9299b881908c77fc1e9aa2e329 completed June 22, 2026, 7:56 a.m.
NED2 Entity disambiguation (via description) batch_6a38eceea1ec8190a5f3a158d37b30ba completed June 22, 2026, 8:06 a.m.
Created at: May 3, 2026, 4:08 p.m.