Triple

T13110622
Position Surface form Disambiguated ID Type / Status
Subject Hof (Saale) E310959 entity
Predicate isServedByMotorway P12245 FINISHED
Object A93
A93 is a German federal motorway (Autobahn) in Bavaria that provides a key north–south connection and links cities such as Hof (Saale) with the wider Autobahn network.
E1023795 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: A93 | Statement: [Hof (Saale), isServedByMotorway, A93]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: A93
Context triple: [Hof (Saale), isServedByMotorway, A93]
  • A. A9
    A9 is a major Swiss motorway that runs across the southwestern part of the country, connecting key regions in Valais and linking to international routes.
  • B. A9
    A9 is a major German autobahn that runs north–south, connecting Berlin with Munich and passing through regions such as Middle Franconia.
  • C. A91
    A91 is a major Italian motorway connecting Rome to Leonardo da Vinci–Fiumicino Airport.
  • D. A92
    A92 is a major trunk road in eastern Scotland that runs along the coast, connecting several key towns and cities including Dundee and Aberdeen.
  • E. A96
    A96 is a major German autobahn in southern Bavaria that connects Munich with Lindau near the Austrian and Swiss borders.
  • 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: A93
Triple: [Hof (Saale), isServedByMotorway, A93]
Generated description
A93 is a German federal motorway (Autobahn) in Bavaria that provides a key north–south connection and links cities such as Hof (Saale) with the wider Autobahn network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: A93
Target entity description: A93 is a German federal motorway (Autobahn) in Bavaria that provides a key north–south connection and links cities such as Hof (Saale) with the wider Autobahn network.
  • A. A9
    A9 is a major Swiss motorway that runs across the southwestern part of the country, connecting key regions in Valais and linking to international routes.
  • B. A9
    A9 is a major German autobahn that runs north–south, connecting Berlin with Munich and passing through regions such as Middle Franconia.
  • C. A91
    A91 is a major Italian motorway connecting Rome to Leonardo da Vinci–Fiumicino Airport.
  • D. A92
    A92 is a major trunk road in eastern Scotland that runs along the coast, connecting several key towns and cities including Dundee and Aberdeen.
  • E. A96
    The A96 is a major trunk road in northeast Scotland that connects the cities of Aberdeen and Inverness, serving as a key route for regional traffic and commerce.
  • 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_69d806a872d08190a329806f8ff30df4 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98bce3678819082a7aa1d83f20592 completed April 10, 2026, 11:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6eadad81c8190881e6577e1c2a207 completed May 3, 2026, 6:27 a.m.
NEDg Description generation batch_69f6ec35b5cc8190a84f522b7808324e completed May 3, 2026, 6:33 a.m.
NED2 Entity disambiguation (via description) batch_69f6ecaf2ed88190b973549bbb3d21ce completed May 3, 2026, 6:35 a.m.
Created at: April 9, 2026, 9:05 p.m.