Triple

T4953641
Position Surface form Disambiguated ID Type / Status
Subject Herbrechtingen E111227 entity
Predicate hasSuburb P747 FINISHED
Object Bissingen
Bissingen is a suburb of the town of Herbrechtingen in the state of Baden-Württemberg, Germany.
 E488113 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: Bissingen | Statement: [Herbrechtingen, hasSuburb, Bissingen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bissingen
Context triple: [Herbrechtingen, hasSuburb, Bissingen]
  • A. 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.
  • B. Miesbach
    Miesbach is a historic town in southern Germany known for its traditional Bavarian culture and picturesque Alpine foothill setting.
  • C. Emsbach
    Emsbach is a small river in Germany that flows through Hesse before joining the Lahn.
  • 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. Hettstadt
    Hettstadt is a small municipality in the Würzburg district of Bavaria, Germany, known for its rural character and proximity to the city of Würzburg.
  • 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: Bissingen
Triple: [Herbrechtingen, hasSuburb, Bissingen]
Generated description
Bissingen is a suburb of the town of Herbrechtingen in the state of Baden-Württemberg, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bissingen
Target entity description: Bissingen is a suburb of the town of Herbrechtingen in the state of Baden-Württemberg, Germany.
  • A. 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.
  • B. Miesbach
    Miesbach is a historic town in southern Germany known for its traditional Bavarian culture and picturesque Alpine foothill setting.
  • C. Emsbach
    Emsbach is a small river in Germany that flows through Hesse before joining the Lahn.
  • 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. Hettstadt
    Hettstadt is a small municipality in the Würzburg district of Bavaria, Germany, known for its rural character and proximity to the city of Würzburg.
  • 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_69bd4418390c8190b7e9766a2512ce55 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd71b82dd88190adfb08c3b3191fe0 completed March 20, 2026, 4:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69be9c4b5608819089c0bf2400395d18 completed March 21, 2026, 1:25 p.m.
NEDg Description generation batch_69be9de82ed48190bb85ba05a2d4ecbe completed March 21, 2026, 1:32 p.m.
NED2 Entity disambiguation (via description) batch_69be9ea74c248190b08113606e43ebc5 completed March 21, 2026, 1:35 p.m.
Created at: March 20, 2026, 1:31 p.m.