Triple

T13230481
Position Surface form Disambiguated ID Type / Status
Subject Paderborn E315002 entity
Predicate twinTown P1072 FINISHED
Object Belleville
Belleville is a city that serves as an international sister city to Paderborn, Germany.
 E732376 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: Belleville | Statement: [Paderborn, twinTown, Belleville]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Belleville
Context triple: [Paderborn, twinTown, Belleville]
  • A. Belleville
    Belleville is a vibrant, historically working-class neighborhood in northeastern Paris known for its multicultural character, street art, and lively food scene.
  • B. Belleville
    Belleville is a small village in south-central Wisconsin, known for its rural character and proximity to the Madison metropolitan area.
  • C. Belleville
    Belleville is a small Canadian city in southeastern Ontario, known as a regional service and commercial hub on the Bay of Quinte.
  • D. Belleville valley
    Belleville valley is a geographical valley region whose waters are collected and carried away by the Doron de Belleville river in the French Alps.
  • E. Saint‑Cloud
    Saint-Cloud is a western suburb of Paris, France, historically notable for its royal château and as the site of key political events during the French Revolution and Napoleonic era.
  • 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: Belleville
Triple: [Paderborn, twinTown, Belleville]
Generated description
Belleville is a city that serves as an international sister city to Paderborn, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Belleville
Target entity description: Belleville is a city that serves as an international sister city to Paderborn, Germany.
  • A. Belleville
    Belleville is a vibrant, historically working-class neighborhood in northeastern Paris known for its multicultural character, street art, and lively food scene.
  • B. Belleville
    Belleville is a small village in south-central Wisconsin, known for its rural character and proximity to the Madison metropolitan area.
  • C. Belleville chosen
    Belleville is a small Canadian city in southeastern Ontario, known as a regional service and commercial hub on the Bay of Quinte.
  • D. Belleville valley
    Belleville valley is a geographical valley region whose waters are collected and carried away by the Doron de Belleville river in the French Alps.
  • E. Saint‑Cloud
    Saint-Cloud is a western suburb of Paris, France, historically notable for its royal château and as the site of key political events during the French Revolution and Napoleonic era.
  • F. None of above.

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_69d806affc688190a25b6ccc588e9c72 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98d336ae08190bfc118cfbefddf84 completed April 10, 2026, 11:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6ff2c07488190ad07c544cca63a7d completed May 3, 2026, 7:54 a.m.
NEDg Description generation batch_69f70408b2088190989c3b38a5d66495 completed May 3, 2026, 8:15 a.m.
NED2 Entity disambiguation (via description) batch_69f70518acc0819089a987abfd42f928 completed May 3, 2026, 8:19 a.m.
Created at: April 9, 2026, 9:21 p.m.