Triple

T28984575
Position Surface form Disambiguated ID Type / Status
Subject Swedish national cross-country skiing team E734642 entity
Predicate notableMember P10 FINISHED
Object Jonna Sundling
Jonna Sundling is a Swedish cross-country skier known for her sprinting prowess and international championship successes, including Olympic and World Championship medals.
E1938686 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: Jonna Sundling | Statement: [Swedish national cross-country skiing team, notableMember, Jonna Sundling]
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: Jonna Sundling
Triple: [Swedish national cross-country skiing team, notableMember, Jonna Sundling]
Generated description
Jonna Sundling is a Swedish cross-country skier known for her sprinting prowess and international championship successes, including Olympic and World Championship medals.

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_69f05b0dd9b481908b7901e1c95ff6b2 completed April 28, 2026, 7 a.m.
NER Named-entity recognition batch_69f65f78c4d08190b68ee2b2fed19fff completed May 2, 2026, 8:32 p.m.
NED1 Entity disambiguation (via context triple) batch_6a28e43bb9848190b26fd1f988d8d43b completed June 10, 2026, 4:12 a.m.
NEDg Description generation batch_6a28e5b9a110819085a4b72809032d62 completed June 10, 2026, 4:19 a.m.
NED2 Entity disambiguation (via description) batch_6a28e63ed86881909fa7b74f66b30ece completed June 10, 2026, 4:21 a.m.
Created at: April 28, 2026, 9:13 a.m.