Triple

T9208407
Position Surface form Disambiguated ID Type / Status
Subject District of Weilheim-Schongau E221046 entity
Predicate containsMunicipality P852 FINISHED
Object Sindelsdorf
Sindelsdorf is a small Bavarian municipality in southern Germany, known for its rural setting near the Alps and its association with early 20th-century Expressionist artists.
 E813633 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: Sindelsdorf | Statement: [District of Weilheim-Schongau, containsMunicipality, Sindelsdorf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sindelsdorf
Context triple: [District of Weilheim-Schongau, containsMunicipality, Sindelsdorf]
  • A. Kiliansdorf
    Kiliansdorf is a village and district of the town of Roth in the Bavarian region of Germany.
  • B. Pottendorf
    Pottendorf is a market town in Lower Austria known for its historic castle and location within the Baden district.
  • C. Teisendorf
    Teisendorf is a market town in southeastern Bavaria, Germany, known for its rural Alpine setting and traditional Bavarian character.
  • D. Siegsdorf
    Siegsdorf is a Bavarian town in southeastern Germany known for its scenic Alpine surroundings and proximity to the Chiemsee lake.
  • E. Gumpoldskirchen
    Gumpoldskirchen is a historic wine-growing town in Lower Austria, renowned for its traditional vineyards and picturesque setting near Vienna.
  • 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: Sindelsdorf
Triple: [District of Weilheim-Schongau, containsMunicipality, Sindelsdorf]
Generated description
Sindelsdorf is a small Bavarian municipality in southern Germany, known for its rural setting near the Alps and its association with early 20th-century Expressionist artists.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sindelsdorf
Target entity description: Sindelsdorf is a small Bavarian municipality in southern Germany, known for its rural setting near the Alps and its association with early 20th-century Expressionist artists.
  • A. Kiliansdorf
    Kiliansdorf is a village and district of the town of Roth in the Bavarian region of Germany.
  • B. Pottendorf
    Pottendorf is a market town in Lower Austria known for its historic castle and location within the Baden district.
  • C. Teisendorf
    Teisendorf is a market town in southeastern Bavaria, Germany, known for its rural Alpine setting and traditional Bavarian character.
  • D. Siegsdorf
    Siegsdorf is a Bavarian town in southeastern Germany known for its scenic Alpine surroundings and proximity to the Chiemsee lake.
  • E. Gumpoldskirchen
    Gumpoldskirchen is a historic wine-growing town in Lower Austria, renowned for its traditional vineyards and picturesque setting near Vienna.
  • 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_69ca83e9d0e081908bdb71097201a06c completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccd9b217008190a0ab4971dd4a8899 completed April 1, 2026, 8:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69d189e115d8819092c3ecbeec8b450f completed April 4, 2026, 10 p.m.
NEDg Description generation batch_69d18aa1e9a48190bf26da5482fd0770 completed April 4, 2026, 10:03 p.m.
NED2 Entity disambiguation (via description) batch_69d18b6a2fb0819092ee274310721b50 completed April 4, 2026, 10:06 p.m.
Created at: March 30, 2026, 7:26 p.m.