Triple

T13691398
Position Surface form Disambiguated ID Type / Status
Subject Unterallgäu E328272 entity
Predicate containsMunicipality P852 FINISHED
Object Dietmannsried
Dietmannsried is a municipality in the Bavarian Allgäu region of southern Germany, known for its rural character and proximity to the Alps.
E1058003 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: Dietmannsried | Statement: [Unterallgäu, containsMunicipality, Dietmannsried]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dietmannsried
Context triple: [Unterallgäu, containsMunicipality, Dietmannsried]
  • A. Biebelried
    Biebelried is a small municipality in the Kitzingen district of Bavaria, Germany, known for its rural character and proximity to the Franconian wine region.
  • B. Eberhardzell
    Eberhardzell is a rural municipality in the district of Biberach in the German state of Baden-Württemberg.
  • C. Steinlach
    Steinlach is a small river in the German state of Baden-Württemberg that flows through the city of Tübingen before joining the Neckar.
  • D. Niederrieden
    Niederrieden is a small municipality in the Unterallgäu district of Bavaria in southern Germany.
  • 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: Dietmannsried
Triple: [Unterallgäu, containsMunicipality, Dietmannsried]
Generated description
Dietmannsried is a municipality in the Bavarian Allgäu region of southern Germany, known for its rural character and proximity to the Alps.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Dietmannsried
Target entity description: Dietmannsried is a municipality in the Bavarian Allgäu region of southern Germany, known for its rural character and proximity to the Alps.
  • A. Biebelried
    Biebelried is a small municipality in the Kitzingen district of Bavaria, Germany, known for its rural character and proximity to the Franconian wine region.
  • B. Eberhardzell
    Eberhardzell is a rural municipality in the district of Biberach in the German state of Baden-Württemberg.
  • C. Steinlach
    Steinlach is a small river in the German state of Baden-Württemberg that flows through the city of Tübingen before joining the Neckar.
  • D. Niederrieden chosen
    Niederrieden is a small municipality in the Unterallgäu district of Bavaria in southern Germany.
  • 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.

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_69d8076ff62081908a7bd79889edd7a0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc8746458819095ec1ba3c01ef31b completed April 12, 2026, 4:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7a8416d808190bd9cb77e0dd0d4be completed May 3, 2026, 7:55 p.m.
NEDg Description generation batch_69f7a994cd688190a077a4854c5c71c9 completed May 3, 2026, 8:01 p.m.
NED2 Entity disambiguation (via description) batch_69f7aa2f696081908f48d44bf7271abc completed May 3, 2026, 8:03 p.m.
Created at: April 9, 2026, 9:53 p.m.