Triple

T31920874
Position Surface form Disambiguated ID Type / Status
Subject Katalin Kovács E814964 entity
Predicate hasMedalRecordIn P89884 FINISHED
Object K-1 events
K-1 events are individual kayak sprint races in which a single paddler competes over various distances on flatwater courses.
 E1985422 NE FINISHED

How this triple was built (3 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: K-1 events | Statement: [Katalin Kovács, hasMedalRecordIn, K-1 events]
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: K-1 events
Triple: [Katalin Kovács, hasMedalRecordIn, K-1 events]
Generated description
K-1 events are individual kayak sprint races in which a single paddler competes over various distances on flatwater courses.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: hasMedalRecordIn
Context triple: [Katalin Kovács, hasMedalRecordIn, K-1 events]
  • A. hasMedalCount
    Indicates the relationship between an entity and the number of medals it possesses or has been awarded.
  • B. hasMedalEquivalent
    Indicates that one medal is considered equivalent in value, status, or recognition to another medal.
  • C. hasMedalComponent
    Indicates that something includes or is composed of a particular medal or medal-related part as one of its components.
  • D. hasMedalEvents chosen
    Indicates that an entity has associated events in which medals are or can be awarded.
  • E. hasMedalForm
    Indicates that one entity is associated with a particular form, type, or version of a medal.
  • F. None of above.

Provenance (6 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_69f348f1df848190851bbfb988da3414 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69fe6e492bf8819080b25221d13445ea completed May 8, 2026, 11:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2e8a34404c8190a624a4adc3e3b8a0 completed June 14, 2026, 11:02 a.m.
NEDg Description generation batch_6a2e8e0350f08190a8de6349c40f023b completed June 14, 2026, 11:18 a.m.
NED2 Entity disambiguation (via description) batch_6a2ea60939988190b06223fbdd05f4fc completed June 14, 2026, 1 p.m.
PD Predicate disambiguation batch_69fe6dd33a6881908fe9bbbc184cab51 completed May 8, 2026, 11:12 p.m.
Created at: May 1, 2026, 12:03 a.m.