Triple

T27695187
Position Surface form Disambiguated ID Type / Status
Subject Schneizlreuth E698271 entity
Predicate hasRoadConnection P385 FINISHED
Object Bundesstraße 21
Bundesstraße 21 is a federal highway in southeastern Germany that runs through the Bavarian Alps, connecting towns near the Austrian border.
E1911829 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: Bundesstraße 21 | Statement: [Schneizlreuth, hasRoadConnection, Bundesstraße 21]
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: Bundesstraße 21
Triple: [Schneizlreuth, hasRoadConnection, Bundesstraße 21]
Generated description
Bundesstraße 21 is a federal highway in southeastern Germany that runs through the Bavarian Alps, connecting towns near the Austrian border.

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_69ef590ea74081908f0cd7500d85fa27 completed April 27, 2026, 12:39 p.m.
NER Named-entity recognition batch_69f6359f02508190911480214dffdc3b completed May 2, 2026, 5:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a277beda02881908240a9a1a66cf365 completed June 9, 2026, 2:35 a.m.
NEDg Description generation batch_6a278388845081908a8cca62166aa482 completed June 9, 2026, 3:07 a.m.
NED2 Entity disambiguation (via description) batch_6a27841b3b7081908394a099970ebac4 completed June 9, 2026, 3:10 a.m.
Created at: April 27, 2026, 2:53 p.m.