Triple

T28342303
Position Surface form Disambiguated ID Type / Status
Subject Nossen E717847 entity
Predicate locatedNear P294 FINISHED
Object A14 motorway
The A14 motorway is a major German autobahn in eastern Germany that connects key cities and transport routes between Saxony, Saxony-Anhalt, and Mecklenburg-Vorpommern.
 E959437 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: A14 motorway | Statement: [Nossen, locatedNear, A14 motorway]
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: A14 motorway
Triple: [Nossen, locatedNear, A14 motorway]
Generated description
The A14 motorway is a major German autobahn in eastern Germany that connects key cities and transport routes between Saxony, Saxony-Anhalt, and Mecklenburg-Vorpommern.

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_69eff6eb30388190b898b96c4be6f49d completed April 27, 2026, 11:53 p.m.
NER Named-entity recognition batch_69f64c04ac408190bab8dfadcc002deb completed May 2, 2026, 7:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7d3e3d48f8819091f26cd3d22e93f6 completed Aug. 13, 2026, 3:47 a.m.
NEDg Description generation batch_6a7d3eac4e80819096e5ff0bff43c693 completed Aug. 13, 2026, 3:49 a.m.
NED2 Entity disambiguation (via description) batch_6a7d3ef97c8c81908d292b7e4d5843a5 completed Aug. 13, 2026, 3:50 a.m.
Created at: April 28, 2026, 12:40 a.m.