Triple

T28972871
Position Surface form Disambiguated ID Type / Status
Subject České Budějovice District E734321 entity
Predicate containsAdministrativeTerritorialEntity P747 FINISHED
Object Hrdějovice
Hrdějovice is a village and municipality in the South Bohemian Region of the Czech Republic, situated near the city of České Budějovice.
E1845538 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: Hrdějovice | Statement: [České Budějovice District, containsAdministrativeTerritorialEntity, Hrdějovice]
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: Hrdějovice
Triple: [České Budějovice District, containsAdministrativeTerritorialEntity, Hrdějovice]
Generated description
Hrdějovice is a village and municipality in the South Bohemian Region of the Czech Republic, situated near the city of České Budějovice.

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_69f05b0d1e7c819092baab93d3fe277e completed April 28, 2026, 7 a.m.
NER Named-entity recognition batch_69f65eddbca081908efdd224d5f49ae4 completed May 2, 2026, 8:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2505accfb88190a1810e8a4976ca3b completed June 7, 2026, 5:46 a.m.
NEDg Description generation batch_6a250ad5af3881908858aa1744eafd5b completed June 7, 2026, 6:08 a.m.
NED2 Entity disambiguation (via description) batch_6a250ea8cdf88190b21bb372ffded6d4 completed June 7, 2026, 6:24 a.m.
Created at: April 28, 2026, 9:06 a.m.