Triple

T28072319
Position Surface form Disambiguated ID Type / Status
Subject Liberec Town Hall E709439 entity
Predicate near P350 FINISHED
Object Liberec Regional Gallery
Liberec Regional Gallery is an art museum in Liberec, Czech Republic, known for its collections of Czech and European art and its role as a major cultural institution in the region.
E1802752 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: Liberec Regional Gallery | Statement: [Liberec Town Hall, near, Liberec Regional Gallery]
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: Liberec Regional Gallery
Triple: [Liberec Town Hall, near, Liberec Regional Gallery]
Generated description
Liberec Regional Gallery is an art museum in Liberec, Czech Republic, known for its collections of Czech and European art and its role as a major cultural institution in the region.

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_69ef9b6f8078819098b741274cd1a2ee completed April 27, 2026, 5:22 p.m.
NER Named-entity recognition batch_69f6403d696081909ff86d174e014d11 completed May 2, 2026, 6:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15c910c4a8819095c5f781916d5291 completed May 26, 2026, 4:23 p.m.
NEDg Description generation batch_6a15cd135198819088bfba729abb28e9 completed May 26, 2026, 4:40 p.m.
NED2 Entity disambiguation (via description) batch_6a15cd8ff1e08190a1e64f8206006dda completed May 26, 2026, 4:42 p.m.
Created at: April 27, 2026, 8:47 p.m.