Triple

T1765996
Position Surface form Disambiguated ID Type / Status
Subject Alb-Donau-Kreis E38763 entity
Predicate hasTown P847 FINISHED
Object Merklingen
Merklingen is a small town in the Alb-Donau district of the German state of Baden-Württemberg.
E247276 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: Merklingen | Statement: [Alb-Donau-Kreis, hasTown, Merklingen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Merklingen
Context triple: [Alb-Donau-Kreis, hasTown, Merklingen]
  • A. Günsberg
    Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
  • B. Hubersdorf
    Hubersdorf is a small municipality located in the canton of Solothurn in northwestern Switzerland.
  • C. Weiterstadt
    Weiterstadt is a town in the German state of Hesse, located near Darmstadt and known for its residential areas and commercial centers.
  • D. Teutschenthal
    Teutschenthal is a municipality in the Saalekreis district of Saxony-Anhalt in central Germany.
  • E. Burkhardtsdorf
    Burkhardtsdorf is a small municipality in the Erzgebirge (Ore Mountains) region of Saxony, eastern Germany.
  • 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: Merklingen
Triple: [Alb-Donau-Kreis, hasTown, Merklingen]
Generated description
Merklingen is a small town in the Alb-Donau district of the German state of Baden-Württemberg.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Merklingen
Target entity description: Merklingen is a small town in the Alb-Donau district of the German state of Baden-Württemberg.
  • A. Günsberg
    Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
  • B. Hubersdorf
    Hubersdorf is a small municipality located in the canton of Solothurn in northwestern Switzerland.
  • C. Weiterstadt
    Weiterstadt is a town in the German state of Hesse, located near Darmstadt and known for its residential areas and commercial centers.
  • D. Teutschenthal
    Teutschenthal is a municipality in the Saalekreis district of Saxony-Anhalt in central Germany.
  • E. Burkhardtsdorf
    Burkhardtsdorf is a small municipality in the Erzgebirge (Ore Mountains) region of Saxony, eastern Germany.
  • 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_69a8862d562481908d7025a1c1f67c0d completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa6467c3f08190abc8a06269ede908 completed March 6, 2026, 5:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae6ae17a808190b5574ca6baafdb71 completed March 9, 2026, 6:38 a.m.
NEDg Description generation batch_69ae6b73bb688190bcade17d991c4862 completed March 9, 2026, 6:40 a.m.
NED2 Entity disambiguation (via description) batch_69ae6be4431c81909c9b4ad82226215d completed March 9, 2026, 6:42 a.m.
Created at: March 4, 2026, 7:31 p.m.