Triple

T30757653
Position Surface form Disambiguated ID Type / Status
Subject German national alpine skiing team E783133 entity
Predicate hasNotableFormerAthlete P87635 FINISHED
Object Katja Seizinger
Katja Seizinger is a former German alpine ski racer and multiple Olympic and World Cup champion, regarded as one of the most successful female skiers in history.
E1934460 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: Katja Seizinger | Statement: [German national alpine skiing team, hasNotableFormerAthlete, Katja Seizinger]
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: Katja Seizinger
Triple: [German national alpine skiing team, hasNotableFormerAthlete, Katja Seizinger]
Generated description
Katja Seizinger is a former German alpine ski racer and multiple Olympic and World Cup champion, regarded as one of the most successful female skiers in history.

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_69f224b047f48190b4f5efeb7ee97b37 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_6a005a8caf0c8190906c666d6be9bf9c completed May 10, 2026, 10:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a28bbd0d15c8190b0459cd2a2e93a14 completed June 10, 2026, 1:20 a.m.
NEDg Description generation batch_6a28bcbbade88190a0782743d0033602 completed June 10, 2026, 1:24 a.m.
NED2 Entity disambiguation (via description) batch_6a28c0d7003881909b928df3a07d09ea completed June 10, 2026, 1:41 a.m.
Created at: April 29, 2026, 8:39 p.m.