Triple

T9859017
Position Surface form Disambiguated ID Type / Status
Subject Coburg district E239658 entity
Predicate contains P35 FINISHED
Object Ahorn
Ahorn is a municipality in the Bavarian region of Germany, known for its rural character and proximity to the city of Coburg.
 E825762 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: Ahorn | Statement: [Coburg district, contains, Ahorn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ahorn
Context triple: [Coburg district, contains, Ahorn]
  • A. Birch
    Birch is a masculine given name most notably borne by American politician Birch Bayh, a long-serving U.S. senator from Indiana.
  • B. Nyssa
    Nyssa is a companion of the Fifth Doctor in the long-running British science fiction television series Doctor Who.
  • C. Beech
    Beech is a small rural village and civil parish in East Hampshire, England, known for its wooded surroundings and residential character.
  • D. Poplar
    Poplar is a small rural community located within the township of Central Manitoulin in Ontario, Canada.
  • E. Poplar
    Poplar is a historic district in the East End of London known for its docklands heritage, post-war social housing, and proximity to Canary Wharf.
  • 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: Ahorn
Triple: [Coburg district, contains, Ahorn]
Generated description
Ahorn is a municipality in the Bavarian region of Germany, known for its rural character and proximity to the city of Coburg.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ahorn
Target entity description: Ahorn is a municipality in the Bavarian region of Germany, known for its rural character and proximity to the city of Coburg.
  • A. Birch
    Birch is a masculine given name most notably borne by American politician Birch Bayh, a long-serving U.S. senator from Indiana.
  • B. Nyssa
    Nyssa is a companion of the Fifth Doctor in the long-running British science fiction television series Doctor Who.
  • C. Beech
    Beech is a small rural village and civil parish in East Hampshire, England, known for its wooded surroundings and residential character.
  • D. Poplar
    Poplar is a small rural community located within the township of Central Manitoulin in Ontario, Canada.
  • E. Poplar
    Poplar is a historic district in the East End of London known for its docklands heritage, post-war social housing, and proximity to Canary Wharf.
  • 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_69ca84e6493081909cf58c8d42ea856b completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb39b06b48190ab53ff00ff0513ca completed April 2, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1e43b2de881909e00f6701d1c7b54 completed April 5, 2026, 4:25 a.m.
NEDg Description generation batch_69d1e5204f748190b1f56ee5469828a2 completed April 5, 2026, 4:29 a.m.
NED2 Entity disambiguation (via description) batch_69d1e598243481909278cb3c911ce3db completed April 5, 2026, 4:31 a.m.
Created at: March 30, 2026, 8:35 p.m.