Triple

T31807620
Position Surface form Disambiguated ID Type / Status
Subject Bundesautobahn 3 E811914 entity
Predicate hasJunctionWith P1018 FINISHED
Object Bundesautobahn 48
Bundesautobahn 48 is a German federal motorway in western Germany that connects the A1 and A3 autobahns, serving as an important regional link through the Eifel and Moselle regions.
E2284404 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: Bundesautobahn 48 | Statement: [Bundesautobahn 3, hasJunctionWith, Bundesautobahn 48]
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: Bundesautobahn 48
Triple: [Bundesautobahn 3, hasJunctionWith, Bundesautobahn 48]
Generated description
Bundesautobahn 48 is a German federal motorway in western Germany that connects the A1 and A3 autobahns, serving as an important regional link through the Eifel and Moselle regions.

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_69f348e846c081908eb468a0665afd55 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6acaf7678819080cc8cc5d0410e0a completed May 3, 2026, 2:02 a.m.
NED1 Entity disambiguation (via context triple) batch_6a438a27783481908df1696aa7f7af5d completed June 30, 2026, 9:19 a.m.
NEDg Description generation batch_6a438b5d9c608190a33ffed9b9ff805e completed June 30, 2026, 9:24 a.m.
NED2 Entity disambiguation (via description) batch_6a438bd204e08190a4ed75eecc35868f completed June 30, 2026, 9:26 a.m.
Created at: April 30, 2026, 11:43 p.m.