Triple

T3259534
Position Surface form Disambiguated ID Type / Status
Subject Strasbourg tramway E68375 entity
Predicate servesDistrict P82 FINISHED
Object Neudorf
Neudorf is a residential district of Strasbourg, France, known for its dense urban fabric, local commerce, and proximity to the city center.
 E355771 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: Neudorf | Statement: [Strasbourg tramway, servesDistrict, Neudorf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Neudorf
Context triple: [Strasbourg tramway, servesDistrict, Neudorf]
  • A. Niendorf
    Niendorf is a residential district in the northwestern part of Hamburg, Germany, known for its suburban character and proximity to Hamburg Airport.
  • B. Reundorf
    Reundorf is a village-level subdivision of the town of Lichtenfels in the Upper Franconia region of Bavaria, Germany.
  • C. Ronsdorf
    Ronsdorf is a district of the German city of Wuppertal in North Rhine-Westphalia, historically known as an independent town in the Bergisches Land region.
  • D. Bergneustadt
    Bergneustadt is a small town in North Rhine-Westphalia, Germany, known for its location in the hilly Oberbergischer Kreis region and its traditional half-timbered architecture.
  • E. Tureberg
    Tureberg is a central district in Sollentuna Municipality, Sweden, known for housing the municipal center and key public services.
  • 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: Neudorf
Triple: [Strasbourg tramway, servesDistrict, Neudorf]
Generated description
Neudorf is a residential district of Strasbourg, France, known for its dense urban fabric, local commerce, and proximity to the city center.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Neudorf
Target entity description: Neudorf is a residential district of Strasbourg, France, known for its dense urban fabric, local commerce, and proximity to the city center.
  • A. Niendorf
    Niendorf is a residential district in the northwestern part of Hamburg, Germany, known for its suburban character and proximity to Hamburg Airport.
  • B. Reundorf
    Reundorf is a village-level subdivision of the town of Lichtenfels in the Upper Franconia region of Bavaria, Germany.
  • C. Ronsdorf
    Ronsdorf is a district of the German city of Wuppertal in North Rhine-Westphalia, historically known as an independent town in the Bergisches Land region.
  • D. Bergneustadt
    Bergneustadt is a small town in North Rhine-Westphalia, Germany, known for its location in the hilly Oberbergischer Kreis region and its traditional half-timbered architecture.
  • E. Tureberg
    Tureberg is a central district in Sollentuna Municipality, Sweden, known for housing the municipal center and key public services.
  • 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_69ad858f74408190bcbd07f967cd7bd0 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adafa4f40c81909adfd0f7f568e3ce completed March 8, 2026, 5:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69b34bb1c468819083b50b5858f8afe0 completed March 12, 2026, 11:26 p.m.
NEDg Description generation batch_69b34ff5a3608190bf8f33ae25b3d1ba completed March 12, 2026, 11:44 p.m.
NED2 Entity disambiguation (via description) batch_69b350b528e4819083497ecfaec5c80d completed March 12, 2026, 11:48 p.m.
Created at: March 8, 2026, 3:09 p.m.