Triple

T8061011
Position Surface form Disambiguated ID Type / Status
Subject Weiterstadt E188118 entity
Predicate hasNeighboringMunicipality P224 FINISHED
Object Griesheim
Griesheim is a town in the German state of Hesse, located near the city of Darmstadt and known for its residential character and local industry.
 E734333 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: Griesheim | Statement: [Weiterstadt, hasNeighboringMunicipality, Griesheim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Griesheim
Context triple: [Weiterstadt, hasNeighboringMunicipality, Griesheim]
  • A. Sulzheim
    Sulzheim is a small municipality in the Schweinfurt district of Lower Franconia in northern Bavaria, Germany.
  • B. Günsberg
    Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
  • C. Rheydt
    Rheydt is a district of the German city of Mönchengladbach in North Rhine-Westphalia, historically an independent town in the Rhineland.
  • D. Gescher
    Gescher is a small town in western Germany’s Münsterland region, noted for its traditional bell foundries and rural character.
  • E. Schweinheim
    Schweinheim is a residential district within the Bad Godesberg borough of Bonn in western Germany.
  • 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: Griesheim
Triple: [Weiterstadt, hasNeighboringMunicipality, Griesheim]
Generated description
Griesheim is a town in the German state of Hesse, located near the city of Darmstadt and known for its residential character and local industry.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Griesheim
Target entity description: Griesheim is a town in the German state of Hesse, located near the city of Darmstadt and known for its residential character and local industry.
  • A. Sulzheim
    Sulzheim is a small municipality in the Schweinfurt district of Lower Franconia in northern Bavaria, Germany.
  • B. Günsberg
    Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
  • C. Rheydt
    Rheydt is a district of the German city of Mönchengladbach in North Rhine-Westphalia, historically an independent town in the Rhineland.
  • D. Gescher
    Gescher is a small town in western Germany’s Münsterland region, noted for its traditional bell foundries and rural character.
  • E. Schweinheim
    Schweinheim is a residential district within the Bad Godesberg borough of Bonn in western Germany.
  • 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_69ca82b2f68881908c50560697e210da completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3fcc61c0819085edc26e75c5f6d5 completed March 31, 2026, 3:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce1c750c7c81908ad680f942bcbe9c completed April 2, 2026, 7:36 a.m.
NEDg Description generation batch_69ce1f64337c8190a78a3d5bb2b9c56e completed April 2, 2026, 7:48 a.m.
NED2 Entity disambiguation (via description) batch_69ce1ff71038819085f0a9d534e06356 completed April 2, 2026, 7:51 a.m.
Created at: March 30, 2026, 5:26 p.m.