Triple

T27037870
Position Surface form Disambiguated ID Type / Status
Subject Městský stadion – Vítkovice Aréna E681105 entity
Predicate locatedIn P40 FINISHED
Object Vítkovice (district of Ostrava)
Vítkovice is a district of the city of Ostrava in the Czech Republic, historically known as an industrial area and now also recognized for its sports and cultural facilities.
E173749 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: Vítkovice (district of Ostrava) | Statement: [Městský stadion – Vítkovice Aréna, locatedIn, Vítkovice (district of Ostrava)]
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: Vítkovice (district of Ostrava)
Triple: [Městský stadion – Vítkovice Aréna, locatedIn, Vítkovice (district of Ostrava)]
Generated description
Vítkovice is a district of the city of Ostrava in the Czech Republic, historically known as an industrial area and now also recognized for its sports and cultural facilities.

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_69eeeb5566f08190813daf896fa3da04 completed April 27, 2026, 4:51 a.m.
NER Named-entity recognition batch_69f62269df6881908d2b4648e4b67ced completed May 2, 2026, 4:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12536a22048190b62bc64001f4dc20 completed May 24, 2026, 1:24 a.m.
NEDg Description generation batch_6a125433c0288190ab1e54c3d763468d completed May 24, 2026, 1:28 a.m.
NED2 Entity disambiguation (via description) batch_6a1254fc697c8190baf4f8adefcea4d2 completed May 24, 2026, 1:31 a.m.
Created at: April 27, 2026, 7:17 a.m.