Triple

T9010323
Position Surface form Disambiguated ID Type / Status
Subject Landkreis Günzburg E215451 entity
Predicate contains P35 FINISHED
Object Thannhausen
Thannhausen is a small town in the Bavarian region of Swabia in southern Germany.
E816015 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: Thannhausen | Statement: [Landkreis Günzburg, contains, Thannhausen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Thannhausen
Context triple: [Landkreis Günzburg, contains, Thannhausen]
  • A. Hademstorf
    Hademstorf is a small municipality in Lower Saxony, Germany, situated in the Heidekreis district.
  • B. Niedernhausen
    Niedernhausen is a municipality in the Rheingau-Taunus district of Hesse, Germany, known for its wooded surroundings in the Taunus hills and convenient rail and road links to Wiesbaden and Frankfurt.
  • C. Ochsenhausen
    Ochsenhausen is a small historic town in the German state of Baden-Württemberg, best known for its former Benedictine monastery, Ochsenhausen Abbey.
  • D. Vellinghausen
    Vellinghausen is a village in western Germany known historically as the site of the Battle of Vellinghausen during the Seven Years' War.
  • E. Irschenhausen
    Irschenhausen is a small village in Bavaria, Germany, known in part as the place where German field marshal Erich von Manstein died.
  • 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: Thannhausen
Triple: [Landkreis Günzburg, contains, Thannhausen]
Generated description
Thannhausen is a small town in the Bavarian region of Swabia in southern Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Thannhausen
Target entity description: Thannhausen is a small town in the Bavarian region of Swabia in southern Germany.
  • A. Hademstorf
    Hademstorf is a small municipality in Lower Saxony, Germany, situated in the Heidekreis district.
  • B. Niedernhausen
    Niedernhausen is a municipality in the Rheingau-Taunus district of Hesse, Germany, known for its wooded surroundings in the Taunus hills and convenient rail and road links to Wiesbaden and Frankfurt.
  • C. Ochsenhausen
    Ochsenhausen is a small historic town in the German state of Baden-Württemberg, best known for its former Benedictine monastery, Ochsenhausen Abbey.
  • D. Vellinghausen
    Vellinghausen is a village in western Germany known historically as the site of the Battle of Vellinghausen during the Seven Years' War.
  • E. Irschenhausen
    Irschenhausen is a small village in Bavaria, Germany, known in part as the place where German field marshal Erich von Manstein died.
  • 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_69d19f50f1c4819099a9c511f58e9873 completed April 4, 2026, 11:31 p.m.
NEDg Description generation batch_69d1a022efd48190b0206bbdf3d93b9e completed April 4, 2026, 11:34 p.m.
NED2 Entity disambiguation (via description) batch_69d1a09ae5b48190b4d0b01cd20ba140 completed April 4, 2026, 11:36 p.m.
Created at: March 30, 2026, 7:06 p.m.