Triple

T9010332
Position Surface form Disambiguated ID Type / Status
Subject Landkreis Günzburg E215451 entity
Predicate contains P35 FINISHED
Object Aislingen
Aislingen is a small municipality in the Bavarian region of Swabia in southern Germany.
E772657 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: Aislingen | Statement: [Landkreis Günzburg, contains, Aislingen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aislingen
Context triple: [Landkreis Günzburg, contains, Aislingen]
  • A. Gaissau
    Gaissau is a small municipality in the Austrian state of Vorarlberg, located near the Rhine River and the border with Switzerland.
  • B. Rauental
    Rauental is a district of the German town of Rastatt in the state of Baden-Württemberg.
  • C. Hausach
    Hausach is a small town in Germany’s Black Forest region, known for its scenic valley setting along the Kinzig River and its traditional timber-framed architecture.
  • D. Miesbach
    Miesbach is a historic town in southern Germany known for its traditional Bavarian culture and picturesque Alpine foothill setting.
  • E. Feldbach
    Feldbach is a small town in southeastern Austria known for its historic center and location in the Styrian volcanic region.
  • 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: Aislingen
Triple: [Landkreis Günzburg, contains, Aislingen]
Generated description
Aislingen is a small municipality in the Bavarian region of Swabia in southern Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Aislingen
Target entity description: Aislingen is a small municipality in the Bavarian region of Swabia in southern Germany.
  • A. Gaissau
    Gaissau is a small municipality in the Austrian state of Vorarlberg, located near the Rhine River and the border with Switzerland.
  • B. Rauental
    Rauental is a district of the German town of Rastatt in the state of Baden-Württemberg.
  • C. Hausach
    Hausach is a small town in Germany’s Black Forest region, known for its scenic valley setting along the Kinzig River and its traditional timber-framed architecture.
  • D. Miesbach
    Miesbach is a historic town in southern Germany known for its traditional Bavarian culture and picturesque Alpine foothill setting.
  • E. Feldbach
    Feldbach is a small town in southeastern Austria known for its historic center and location in the Styrian volcanic region.
  • 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_69ca83a2bf088190986ee7a8eb90407d completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc69c00ae8819090786385a72e8baf completed April 1, 2026, 12:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfdb9dca848190952427bb5712081f completed April 3, 2026, 3:24 p.m.
NEDg Description generation batch_69cfdc5b230881908057cc868e44ea44 completed April 3, 2026, 3:27 p.m.
NED2 Entity disambiguation (via description) batch_69cfdcfc28288190b849b3f0216a7e9a completed April 3, 2026, 3:30 p.m.
Created at: March 30, 2026, 7:06 p.m.