Triple

T14732626
Position Surface form Disambiguated ID Type / Status
Subject Iserlohn E346114 entity
Predicate locatedNearMotorway P385 FINISHED
Object A46
The A46 is a major German autobahn in North Rhine-Westphalia that connects several cities in the Ruhr region and Sauerland, facilitating regional east–west traffic.
 E1116788 NE FINISHED

How this triple was built (4 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: A46 | Statement: [Iserlohn, locatedNearMotorway, A46]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: A46
Context triple: [Iserlohn, locatedNearMotorway, A46]
  • A. A46
    A46 is a major trunk road in England that runs from Bath in the southwest to Cleethorpes on the east coast, connecting several key cities and regions.
  • B. A465
    A465 is a major trunk road in Wales that connects several key towns and regions, including the area around Tredegar.
  • C. A48
    The A48 is a major road in South Wales that serves as a key route linking Cardiff with other towns and cities in the region.
  • D. A47
    The A47 is a major road in the United Kingdom that runs across eastern England, linking Birmingham and the Midlands to cities such as Leicester, Peterborough, and Great Yarmouth.
  • E. A406
    A406 is a major ring road in London, commonly known as part of the North Circular Road, carrying heavy traffic around the northern suburbs of the city.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: A46
Triple: [Iserlohn, locatedNearMotorway, A46]
Generated description
The A46 is a major German autobahn in North Rhine-Westphalia that connects several cities in the Ruhr region and Sauerland, facilitating regional east–west traffic.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: A46
Target entity description: The A46 is a major German autobahn in North Rhine-Westphalia that connects several cities in the Ruhr region and Sauerland, facilitating regional east–west traffic.
  • A. A46
    A46 is a major trunk road in England that runs from Bath in the southwest to Cleethorpes on the east coast, connecting several key cities and regions.
  • B. A465
    A465 is a major trunk road in Wales that connects several key towns and regions, including the area around Tredegar.
  • C. A48
    The A48 is a major road in South Wales that serves as a key route linking Cardiff with other towns and cities in the region.
  • D. A47
    The A47 is a major road in the United Kingdom that runs across eastern England, linking Birmingham and the Midlands to cities such as Leicester, Peterborough, and Great Yarmouth.
  • E. A406
    A406 is a major ring road in London, commonly known as part of the North Circular Road, carrying heavy traffic around the northern suburbs of the city.
  • F. None of above. chosen

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_69d822e5911c8190ba589f957dbd9ba7 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec72ea9348190817efcdaa973d7f7 completed April 14, 2026, 11:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdfb8bcc188190901e3f692fd8fbf9 completed May 8, 2026, 3:04 p.m.
NEDg Description generation batch_69fdfe396bb48190ade10c757a3a7e5e completed May 8, 2026, 3:16 p.m.
NED2 Entity disambiguation (via description) batch_69fdfeb5d08081908ff0fdbc489fc985 completed May 8, 2026, 3:18 p.m.
Created at: April 10, 2026, 1:29 a.m.