Triple

T4254833
Position Surface form Disambiguated ID Type / Status
Subject Szentendre E95946 entity
Predicate hasTwinTown P919 FINISHED
Object Herrenberg
Herrenberg is a historic town in the German state of Baden-Württemberg, known for its well-preserved medieval center and proximity to the Schönbuch Nature Park.
 E458163 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: Herrenberg | Statement: [Szentendre, hasTwinTown, Herrenberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Herrenberg
Context triple: [Szentendre, hasTwinTown, Herrenberg]
  • A. Günsberg
    Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
  • B. Miesbach
    Miesbach is a historic town in southern Germany known for its traditional Bavarian culture and picturesque Alpine foothill setting.
  • C. Vellinghausen
    Vellinghausen is a village in western Germany known historically as the site of the Battle of Vellinghausen during the Seven Years' War.
  • D. Gernsbach
    Gernsbach is a historic town in southwestern Germany’s Black Forest region, known for its medieval old town and picturesque setting along the Murg River.
  • E. Kuppenheim
    Kuppenheim is a small town in the Rastatt district of Baden-Württemberg, southwestern Germany, situated near the Black Forest.
  • 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: Herrenberg
Triple: [Szentendre, hasTwinTown, Herrenberg]
Generated description
Herrenberg is a historic town in the German state of Baden-Württemberg, known for its well-preserved medieval center and proximity to the Schönbuch Nature Park.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Herrenberg
Target entity description: Herrenberg is a historic town in the German state of Baden-Württemberg, known for its well-preserved medieval center and proximity to the Schönbuch Nature Park.
  • A. Günsberg
    Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
  • B. Miesbach
    Miesbach is a historic town in southern Germany known for its traditional Bavarian culture and picturesque Alpine foothill setting.
  • C. Vellinghausen
    Vellinghausen is a village in western Germany known historically as the site of the Battle of Vellinghausen during the Seven Years' War.
  • D. Gernsbach
    Gernsbach is a historic town in southwestern Germany’s Black Forest region, known for its medieval old town and picturesque setting along the Murg River.
  • E. Kuppenheim
    Kuppenheim is a small town in the Rastatt district of Baden-Württemberg, southwestern Germany, situated near the Black Forest.
  • 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_69b3453f759881909b91f01a1e82c036 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34ec036e8819087d8585170707545 completed March 12, 2026, 11:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfa0121b48190899cb4be8b87a93b completed March 21, 2026, 1:53 a.m.
NEDg Description generation batch_69bdfb36a18481908bb566db970b101a completed March 21, 2026, 1:58 a.m.
NED2 Entity disambiguation (via description) batch_69bdfbc9bea48190a8a0bf13c6fa7191 completed March 21, 2026, 2 a.m.
Created at: March 12, 2026, 11:06 p.m.