Triple

T34598903
Position Surface form Disambiguated ID Type / Status
Subject Trutnov District E888398 entity
Predicate hasMunicipality P847 FINISHED
Object Dolní Branná
Dolní Branná is a small village and municipality in the Hradec Králové Region of the Czech Republic, known for its rural character in the foothills of the Krkonoše (Giant) Mountains.
E2108896 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: Dolní Branná | Statement: [Trutnov District, hasMunicipality, Dolní Branná]
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: Dolní Branná
Triple: [Trutnov District, hasMunicipality, Dolní Branná]
Generated description
Dolní Branná is a small village and municipality in the Hradec Králové Region of the Czech Republic, known for its rural character in the foothills of the Krkonoše (Giant) Mountains.

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_69f349d3bfcc81909874c99e646fb3ea completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f72162b76c819096138d6bc13f6253 completed May 3, 2026, 10:20 a.m.
NED1 Entity disambiguation (via context triple) batch_6a375bcc8cf88190a3bdbc86c9d606f3 completed June 21, 2026, 3:34 a.m.
NEDg Description generation batch_6a375c9bba008190abd41299791ed996 completed June 21, 2026, 3:38 a.m.
NED2 Entity disambiguation (via description) batch_6a375d2b3c308190b2dc3e3d805005ce completed June 21, 2026, 3:40 a.m.
Created at: May 1, 2026, 2:03 a.m.