Triple

T9641627
Position Surface form Disambiguated ID Type / Status
Subject Fürstenfeldbruck district E233084 entity
Predicate contains P35 FINISHED
Object Mammendorf
Mammendorf is a municipality in Upper Bavaria, Germany, known for its rural character and proximity to the city of Munich.
 E903858 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: Mammendorf | Statement: [Fürstenfeldbruck district, contains, Mammendorf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mammendorf
Context triple: [Fürstenfeldbruck district, contains, Mammendorf]
  • A. Hägendorf
    Hägendorf is a municipality in the canton of Solothurn in northwestern Switzerland, known for its residential character and proximity to the Jura mountains.
  • B. Hunderdorf
    Hunderdorf is a small municipality in the Straubing-Bogen district of Lower Bavaria in southeastern Germany.
  • C. Mensdorf
    Mensdorf is a small village in eastern Luxembourg that forms part of the commune of Betzdorf.
  • D. Siegsdorf
    Siegsdorf is a Bavarian town in southeastern Germany known for its scenic Alpine surroundings and proximity to the Chiemsee lake.
  • E. Biendorf
    Biendorf is a small municipality in northern Germany notable as the birthplace of German Field Marshal Helmuth von Moltke the Younger.
  • 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: Mammendorf
Triple: [Fürstenfeldbruck district, contains, Mammendorf]
Generated description
Mammendorf is a 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: Mammendorf
Target entity description: Mammendorf is a municipality in Upper Bavaria, Germany, known for its rural character and proximity to the city of Munich.
  • A. Hägendorf
    Hägendorf is a municipality in the canton of Solothurn in northwestern Switzerland, known for its residential character and proximity to the Jura mountains.
  • B. Hunderdorf
    Hunderdorf is a small municipality in the Straubing-Bogen district of Lower Bavaria in southeastern Germany.
  • C. Mensdorf
    Mensdorf is a small village in eastern Luxembourg that forms part of the commune of Betzdorf.
  • D. Siegsdorf
    Siegsdorf is a Bavarian town in southeastern Germany known for its scenic Alpine surroundings and proximity to the Chiemsee lake.
  • E. Biendorf
    Biendorf is a small municipality in northern Germany notable as the birthplace of German Field Marshal Helmuth von Moltke the Younger.
  • 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_69e3e686db808190a2aa975a20e69696 completed April 18, 2026, 8:16 p.m.
NEDg Description generation batch_69e3f2c889dc81909a04c1db0509e3d9 completed April 18, 2026, 9:08 p.m.
NED2 Entity disambiguation (via description) batch_69e3f4746dbc8190a0e28202ad5e6b4f completed April 18, 2026, 9:15 p.m.
Created at: March 30, 2026, 8:12 p.m.