Triple

T25403657
Position Surface form Disambiguated ID Type / Status
Subject Znojmo District E636494 entity
Predicate containsTown P847 FINISHED
Object Vranov nad Dyjí
Vranov nad Dyjí is a small historic town in the South Moravian Region of the Czech Republic, known for its picturesque chateau overlooking the Dyje River and its proximity to Podyjí National Park.
E1752644 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: Vranov nad Dyjí | Statement: [Znojmo District, containsTown, Vranov nad Dyjí]
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: Vranov nad Dyjí
Triple: [Znojmo District, containsTown, Vranov nad Dyjí]
Generated description
Vranov nad Dyjí is a small historic town in the South Moravian Region of the Czech Republic, known for its picturesque chateau overlooking the Dyje River and its proximity to Podyjí National Park.

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_69e75db361d881908d8701c856da6413 completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f584fcac20819093a4919df2ef23b6 completed May 2, 2026, 5 a.m.
NED1 Entity disambiguation (via context triple) batch_6a123a83a1ac81908c2ad708ee7b4bf4 completed May 23, 2026, 11:38 p.m.
NEDg Description generation batch_6a123b0bc16c81909f16cfe68591d543 completed May 23, 2026, 11:40 p.m.
NED2 Entity disambiguation (via description) batch_6a123b77a8fc81908f90c82b59350cfd completed May 23, 2026, 11:42 p.m.
Created at: April 21, 2026, 1:52 p.m.