Triple

T9672979
Position Surface form Disambiguated ID Type / Status
Subject Zurbriggen E234073 entity
Predicate hasNotableBearer P458 FINISHED
Object Elia Zurbriggen
Elia Zurbriggen is a Swiss alpine skier known for competing in international skiing competitions.
E816102 NE FINISHED

How this triple was built (4 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: Elia Zurbriggen | Statement: [Zurbriggen, hasNotableBearer, Elia Zurbriggen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elia Zurbriggen
Context triple: [Zurbriggen, hasNotableBearer, Elia Zurbriggen]
  • A. Heidi Zurbriggen
    Heidi Zurbriggen is a former Swiss alpine skier who competed at the international level in the late 20th century.
  • B. Pirmin Zurbriggen
    Pirmin Zurbriggen is a retired Swiss alpine ski racer who dominated the sport in the 1980s, winning multiple World Cup overall titles and an Olympic gold medal.
  • C. Lara Gut-Behrami
    Lara Gut-Behrami is a Swiss World Cup alpine ski racer and Olympic champion known for her success in speed events such as super-G and downhill.
  • D. Miroslava Federer
    Miroslava Federer is a former Slovak-born Swiss professional tennis player and the wife of tennis legend Roger Federer.
  • E. Marie-José Clivaz
    Marie-José Clivaz is an educator and school leader best known for co-founding the international private school Collège du Léman in Switzerland.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Elia Zurbriggen
Triple: [Zurbriggen, hasNotableBearer, Elia Zurbriggen]
Generated description
Elia Zurbriggen is a Swiss alpine skier known for competing in international skiing competitions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Elia Zurbriggen
Target entity description: Elia Zurbriggen is a Swiss alpine skier known for competing in international skiing competitions.
  • A. Heidi Zurbriggen
    Heidi Zurbriggen is a former Swiss alpine skier who competed at the international level in the late 20th century.
  • B. Pirmin Zurbriggen
    Pirmin Zurbriggen is a retired Swiss alpine ski racer who dominated the sport in the 1980s, winning multiple World Cup overall titles and an Olympic gold medal.
  • C. Lara Gut-Behrami
    Lara Gut-Behrami is a Swiss World Cup alpine ski racer and Olympic champion known for her success in speed events such as super-G and downhill.
  • D. Miroslava Federer
    Miroslava Federer is a former Slovak-born Swiss professional tennis player and the wife of tennis legend Roger Federer.
  • E. Marie-José Clivaz
    Marie-José Clivaz is an educator and school leader best known for co-founding the international private school Collège du Léman in Switzerland.
  • F. None of above. chosen

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_69ca848f55e48190b3f67252571c3d45 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9c6aa01c819083fc758470096ec2 completed April 1, 2026, 10:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69d19f70597c81909d461b3d935b02a5 completed April 4, 2026, 11:32 p.m.
NEDg Description generation batch_69d1a022efd48190b0206bbdf3d93b9e completed April 4, 2026, 11:34 p.m.
NED2 Entity disambiguation (via description) batch_69d1a09ae5b48190b4d0b01cd20ba140 completed April 4, 2026, 11:36 p.m.
Created at: March 30, 2026, 8:15 p.m.