Triple

T36352944
Position Surface form Disambiguated ID Type / Status
Subject Sanok Castle E895256 entity
Predicate operatedBy P86 FINISHED
Object Historical Museum in Sanok
The Historical Museum in Sanok is a major regional museum in southeastern Poland renowned for its extensive collections of Orthodox and Catholic religious art, including one of the largest icon collections in the country.
E2180745 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: Historical Museum in Sanok | Statement: [Sanok Castle, operatedBy, Historical Museum in Sanok]
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: Historical Museum in Sanok
Triple: [Sanok Castle, operatedBy, Historical Museum in Sanok]
Generated description
The Historical Museum in Sanok is a major regional museum in southeastern Poland renowned for its extensive collections of Orthodox and Catholic religious art, including one of the largest icon collections in the country.

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_69f76e4f437c8190a1af3ea2564f41f5 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7bac3cf088190ba6e7beae92e7a17 completed May 3, 2026, 9:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39a329e2488190b39d42dd7112a793 completed June 22, 2026, 9:03 p.m.
NEDg Description generation batch_6a39a4608b3481909ecc1119384ef337 completed June 22, 2026, 9:08 p.m.
NED2 Entity disambiguation (via description) batch_6a39a599bce88190950bc55a2e74ea29 completed June 22, 2026, 9:14 p.m.
Created at: May 3, 2026, 4:09 p.m.