Triple

T35397403
Position Surface form Disambiguated ID Type / Status
Subject RK Gorenje Velenje E1023118 entity
Predicate alsoKnownAs P39 FINISHED
Object Rokometni klub Gorenje Velenje
Rokometni klub Gorenje Velenje is a professional handball club from Velenje, Slovenia, known as one of the country’s most successful and regularly competing in domestic and European competitions.
E2139569 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: Rokometni klub Gorenje Velenje | Statement: [RK Gorenje Velenje, alsoKnownAs, Rokometni klub Gorenje Velenje]
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: Rokometni klub Gorenje Velenje
Triple: [RK Gorenje Velenje, alsoKnownAs, Rokometni klub Gorenje Velenje]
Generated description
Rokometni klub Gorenje Velenje is a professional handball club from Velenje, Slovenia, known as one of the country’s most successful and regularly competing in domestic and European competitions.

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_69f76df43ca4819098711ca4370f1bb9 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7953741f88190bf96763ffef5aa4b completed May 3, 2026, 6:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a382cc920d48190af228a2888b41815 completed June 21, 2026, 6:26 p.m.
NEDg Description generation batch_6a382d87c1fc8190b08fdc28a621e0f8 completed June 21, 2026, 6:29 p.m.
NED2 Entity disambiguation (via description) batch_6a382e5f437481909c6c9f085168bfec completed June 21, 2026, 6:33 p.m.
Created at: May 3, 2026, 4:03 p.m.