Triple

T26547855
Position Surface form Disambiguated ID Type / Status
Subject Oskar von Miller E671588 entity
Predicate familyName P18 FINISHED
Object von Miller
Von Miller is an American football outside linebacker, best known for his dominant pass-rushing career in the NFL and his Super Bowl 50 MVP performance with the Denver Broncos.
 E1730962 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: von Miller | Statement: [Oskar von Miller, familyName, von Miller]
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: von Miller
Triple: [Oskar von Miller, familyName, von Miller]
Generated description
Von Miller is an American football outside linebacker, best known for his dominant pass-rushing career in the NFL and his Super Bowl 50 MVP performance with the Denver Broncos.

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_69eeb32163f08190af5f81282738e27a completed April 27, 2026, 12:51 a.m.
NER Named-entity recognition batch_69f61436eee08190a23739d9347ec088 completed May 2, 2026, 3:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11c819b32c8190aaca1f8db245732e completed May 23, 2026, 3:30 p.m.
NEDg Description generation batch_6a11c966cc288190804da81d474872dd completed May 23, 2026, 3:36 p.m.
NED2 Entity disambiguation (via description) batch_6a11ca7256dc81908499e290c0b32b39 completed May 23, 2026, 3:40 p.m.
Created at: April 27, 2026, 1:45 a.m.