Triple

T15838661
Position Surface form Disambiguated ID Type / Status
Subject Samtgemeinde Faßberg E384045 entity
Predicate locatedNear P294 FINISHED
Object Eschede
Eschede is a municipality in Lower Saxony, Germany, known for its rural setting and the site of the 1998 ICE high-speed train disaster.
 E1179643 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: Eschede | Statement: [Samtgemeinde Faßberg, locatedNear, Eschede]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Eschede
Context triple: [Samtgemeinde Faßberg, locatedNear, Eschede]
  • A. Eschen
    Eschen is a municipality in northern Liechtenstein known for its residential character and role as one of the country’s larger population centers.
  • B. Haslach
    Haslach is a district or locality that forms part of the town of Oberkirch in the German state of Baden-Württemberg.
  • C. Haslach
    Haslach is a town in southern Germany historically noted as the site of the Battle of Haslach-Jungingen during the Napoleonic Wars.
  • D. Salvenach
    Salvenach is a former municipality in the canton of Fribourg in western Switzerland, known for its rural character and proximity to the town of Murten.
  • E. Sossenheim
    Sossenheim is a district in the west of Frankfurt am Main, Germany, known for its residential character and proximity to the Main River industrial areas.
  • 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: Eschede
Triple: [Samtgemeinde Faßberg, locatedNear, Eschede]
Generated description
Eschede is a municipality in Lower Saxony, Germany, known for its rural setting and the site of the 1998 ICE high-speed train disaster.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Eschede
Target entity description: Eschede is a municipality in Lower Saxony, Germany, known for its rural setting and the site of the 1998 ICE high-speed train disaster.
  • A. Eschen
    Eschen is a municipality in northern Liechtenstein known for its residential character and role as one of the country’s larger population centers.
  • B. Haslach
    Haslach is a district or locality that forms part of the town of Oberkirch in the German state of Baden-Württemberg.
  • C. Haslach
    Haslach is a town in southern Germany historically noted as the site of the Battle of Haslach-Jungingen during the Napoleonic Wars.
  • D. Salvenach
    Salvenach is a former municipality in the canton of Fribourg in western Switzerland, known for its rural character and proximity to the town of Murten.
  • E. Sossenheim
    Sossenheim is a district in the west of Frankfurt am Main, Germany, known for its residential character and proximity to the Main River industrial areas.
  • 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_69d86da34c888190976e06c4019d415a completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e142e4fa24819086a1a226082ac2d3 completed April 16, 2026, 8:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffa13c931481908ed9fd10fddd867c completed May 9, 2026, 9:03 p.m.
NEDg Description generation batch_69ffa419c6dc81908c9678f8434530f8 completed May 9, 2026, 9:16 p.m.
NED2 Entity disambiguation (via description) batch_69ffa4cff5088190a7f11fd62941f4fb completed May 9, 2026, 9:19 p.m.
Created at: April 10, 2026, 4:49 a.m.