Triple

T9099523
Position Surface form Disambiguated ID Type / Status
Subject Rheingau E218115 entity
Predicate hasSubregion P285 FINISHED
Object Assmannshausen
Assmannshausen is a renowned wine-producing village in Germany’s Rheingau region, particularly famous for its red wines made from Spätburgunder (Pinot Noir).
 E826743 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: Assmannshausen | Statement: [Rheingau, hasSubregion, Assmannshausen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Assmannshausen
Context triple: [Rheingau, hasSubregion, Assmannshausen]
  • A. Balzhausen
    Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
  • B. Ochsenhausen
    Ochsenhausen is a small historic town in the German state of Baden-Württemberg, best known for its former Benedictine monastery, Ochsenhausen Abbey.
  • C. Waigolshausen
    Waigolshausen is a small municipality in the Schweinfurt district of Bavaria, Germany, known for its rural character and location in the Franconian region.
  • 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. Deisenhausen
    Deisenhausen is a small municipality in the Bavarian region of Swabia in southern 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: Assmannshausen
Triple: [Rheingau, hasSubregion, Assmannshausen]
Generated description
Assmannshausen is a renowned wine-producing village in Germany’s Rheingau region, particularly famous for its red wines made from Spätburgunder (Pinot Noir).
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Assmannshausen
Target entity description: Assmannshausen is a renowned wine-producing village in Germany’s Rheingau region, particularly famous for its red wines made from Spätburgunder (Pinot Noir).
  • A. Balzhausen
    Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
  • B. Ochsenhausen
    Ochsenhausen is a small historic town in the German state of Baden-Württemberg, best known for its former Benedictine monastery, Ochsenhausen Abbey.
  • C. Waigolshausen
    Waigolshausen is a small municipality in the Schweinfurt district of Bavaria, Germany, known for its rural character and location in the Franconian region.
  • 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. Deisenhausen
    Deisenhausen is a small municipality in the Bavarian region of Swabia in southern 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_69ca83d9844081908e561e367fda6d45 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc9710ac04819096b9c8d3399b9c35 completed April 1, 2026, 3:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1e3e1ac348190aec39a41b8b113dc completed April 5, 2026, 4:24 a.m.
NEDg Description generation batch_69d1e582a71c8190a7b67d37733db4aa completed April 5, 2026, 4:30 a.m.
NED2 Entity disambiguation (via description) batch_69d1e617cdf88190bbc4cb733cbdd43b completed April 5, 2026, 4:33 a.m.
Created at: March 30, 2026, 7:15 p.m.