Triple

T34041367
Position Surface form Disambiguated ID Type / Status
Subject D10 motorway via Benátky nad Jizerou E872953 entity
Predicate passesThrough P225 FINISHED
Object Benátky nad Jizerou
Benátky nad Jizerou is a small historic town in the Central Bohemian Region of the Czech Republic, situated on the Jizera River northeast of Prague.
E2213926 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: Benátky nad Jizerou | Statement: [D10 motorway via Benátky nad Jizerou, passesThrough, Benátky nad Jizerou]
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: Benátky nad Jizerou
Triple: [D10 motorway via Benátky nad Jizerou, passesThrough, Benátky nad Jizerou]
Generated description
Benátky nad Jizerou is a small historic town in the Central Bohemian Region of the Czech Republic, situated on the Jizera River northeast of Prague.

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_69f349a3363081909cea4c9a848cefe2 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f70b40e3d081908d542f27358f1ed3 completed May 3, 2026, 8:45 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3f69ef12b48190a1373909899f24f1 completed June 27, 2026, 6:13 a.m.
NEDg Description generation batch_6a3f6b68b16c819098b8a23407c6de19 completed June 27, 2026, 6:19 a.m.
NED2 Entity disambiguation (via description) batch_6a3f6bfc11b881909dcb875cc92f5535 completed June 27, 2026, 6:21 a.m.
Created at: May 1, 2026, 1:51 a.m.