Triple

T28755422
Position Surface form Disambiguated ID Type / Status
Subject Kunětická Hora Castle E731656 entity
Predicate managedBy P86 FINISHED
Object Pardubice Museum
Pardubice Museum is a regional cultural and historical museum in the Czech Republic that preserves and presents the heritage of the Pardubice area through exhibitions, collections, and educational activities.
E1834209 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: Pardubice Museum | Statement: [Kunětická Hora Castle, managedBy, Pardubice Museum]
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: Pardubice Museum
Triple: [Kunětická Hora Castle, managedBy, Pardubice Museum]
Generated description
Pardubice Museum is a regional cultural and historical museum in the Czech Republic that preserves and presents the heritage of the Pardubice area through exhibitions, collections, and educational activities.

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_69f043ed68a881909e858a06bab7a247 completed April 28, 2026, 5:21 a.m.
NER Named-entity recognition batch_69f657fb2bc48190882778ab59298445 completed May 2, 2026, 8 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24a256e6e48190a8ebf66e15001425 completed June 6, 2026, 10:42 p.m.
NEDg Description generation batch_6a24a695a9988190bd815507f8027193 completed June 6, 2026, 11 p.m.
NED2 Entity disambiguation (via description) batch_6a24aab9053081909350507082946a76 completed June 6, 2026, 11:18 p.m.
Created at: April 28, 2026, 6:09 a.m.