Triple

T9641635
Position Surface form Disambiguated ID Type / Status
Subject Fürstenfeldbruck district E233084 entity
Predicate contains P35 FINISHED
Object Schöngeising
Schöngeising is a small municipality in Upper Bavaria, Germany, known for its rural character and proximity to the city of Munich.
 E863892 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: Schöngeising | Statement: [Fürstenfeldbruck district, contains, Schöngeising]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Schöngeising
Context triple: [Fürstenfeldbruck district, contains, Schöngeising]
  • A. Geretsried
    Geretsried is a town in Upper Bavaria, Germany, situated on the Isar River and known as the largest town in the Bad Tölz-Wolfratshausen district.
  • B. Neusäß
    Neusäß is a town in Bavaria, Germany, located just northwest of the city of Augsburg and functioning largely as a residential and commuter suburb.
  • C. Eggenfelden
    Eggenfelden is a town in southeastern Germany known as a local commercial and cultural center within the region of Lower Bavaria.
  • D. Schneizlreuth
    Schneizlreuth is a small Bavarian municipality in southeastern Germany, known for its alpine landscapes and location near the Austrian border.
  • E. Kirchlindach
    Kirchlindach is a Swiss municipality in the canton of Bern, known for its rural character and proximity to the city of Bern.
  • 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: Schöngeising
Triple: [Fürstenfeldbruck district, contains, Schöngeising]
Generated description
Schöngeising is a small municipality in Upper Bavaria, Germany, known for its rural character and proximity to the city of Munich.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Schöngeising
Target entity description: Schöngeising is a small municipality in Upper Bavaria, Germany, known for its rural character and proximity to the city of Munich.
  • A. Geretsried
    Geretsried is a town in Upper Bavaria, Germany, situated on the Isar River and known as the largest town in the Bad Tölz-Wolfratshausen district.
  • B. Neusäß
    Neusäß is a town in Bavaria, Germany, located just northwest of the city of Augsburg and functioning largely as a residential and commuter suburb.
  • C. Eggenfelden
    Eggenfelden is a town in southeastern Germany known as a local commercial and cultural center within the region of Lower Bavaria.
  • D. Schneizlreuth
    Schneizlreuth is a small Bavarian municipality in southeastern Germany, known for its alpine landscapes and location near the Austrian border.
  • E. Kirchlindach
    Kirchlindach is a Swiss municipality in the canton of Bern, known for its rural character and proximity to the city of Bern.
  • 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_69ca848a5a908190aad251f4137b0c3a completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9b566a2881909ab3f9502b1c3c8d completed April 1, 2026, 10:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69d87e177fcc81908613409c03995ea8 completed April 10, 2026, 4:35 a.m.
NEDg Description generation batch_69d886c325c4819089dac35eb26e7961 completed April 10, 2026, 5:12 a.m.
NED2 Entity disambiguation (via description) batch_69d88dbbe97c8190861e08f3ff39f91b completed April 10, 2026, 5:42 a.m.
Created at: March 30, 2026, 8:12 p.m.