Triple

T24692282
Position Surface form Disambiguated ID Type / Status
Subject FIL World Luge Championships 2008 E611473 entity
Predicate hasParticipant P149 FINISHED
Object Torsten Wustlich
Torsten Wustlich is a German luger who competed at the international level, winning multiple World Championship titles in men's doubles.
E1648855 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: Torsten Wustlich | Statement: [FIL World Luge Championships 2008, hasParticipant, Torsten Wustlich]
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: Torsten Wustlich
Triple: [FIL World Luge Championships 2008, hasParticipant, Torsten Wustlich]
Generated description
Torsten Wustlich is a German luger who competed at the international level, winning multiple World Championship titles in men's doubles.

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_69e2c4d678b081908910f4271627a31a completed April 17, 2026, 11:40 p.m.
NER Named-entity recognition batch_69f40fd8f45c8190b6c30ed81338d380 completed May 1, 2026, 2:28 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1010048c04819085a2faf541c83cbf completed May 22, 2026, 8:12 a.m.
NEDg Description generation batch_6a10136aa8948190b19d212e087b3f35 completed May 22, 2026, 8:27 a.m.
NED2 Entity disambiguation (via description) batch_6a1015013f6c8190be31319e5c05c3f4 completed May 22, 2026, 8:34 a.m.
Created at: April 18, 2026, 3:21 a.m.