Triple

T3297974
Position Surface form Disambiguated ID Type / Status
Subject Breg E69261 entity
Predicate flowsThrough P225 FINISHED
Object Bräunlingen
Bräunlingen is a small historic town in the Black Forest region of Baden-Württemberg, Germany, known for its picturesque setting and traditional architecture.
 E347447 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: Bräunlingen | Statement: [Breg, flowsThrough, Bräunlingen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bräunlingen
Context triple: [Breg, flowsThrough, Bräunlingen]
  • A. Miesbach
    Miesbach is a historic town in southern Germany known for its traditional Bavarian culture and picturesque Alpine foothill setting.
  • B. Emsbach
    Emsbach is a small river in Germany that flows through Hesse before joining the Lahn.
  • C. Lampoldshausen
    Lampoldshausen is a German village best known as a major site for rocket propulsion research and testing facilities of the German Aerospace Center.
  • D. Laichingen
    Laichingen is a small town in the Alb-Donau district of Baden-Württemberg in southern Germany, known for its location on the Swabian Jura plateau and its historic textile industry.
  • E. Röthenbach
    Röthenbach is a station in Nuremberg, Germany that serves as a terminus on the city’s U-Bahn rapid transit network.
  • 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: Bräunlingen
Triple: [Breg, flowsThrough, Bräunlingen]
Generated description
Bräunlingen is a small historic town in the Black Forest region of Baden-Württemberg, Germany, known for its picturesque setting and traditional architecture.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bräunlingen
Target entity description: Bräunlingen is a small historic town in the Black Forest region of Baden-Württemberg, Germany, known for its picturesque setting and traditional architecture.
  • A. Miesbach
    Miesbach is a historic town in southern Germany known for its traditional Bavarian culture and picturesque Alpine foothill setting.
  • B. Emsbach
    Emsbach is a small river in Germany that flows through Hesse before joining the Lahn.
  • C. Lampoldshausen
    Lampoldshausen is a German village best known as a major site for rocket propulsion research and testing facilities of the German Aerospace Center.
  • D. Laichingen
    Laichingen is a small town in the Alb-Donau district of Baden-Württemberg in southern Germany, known for its location on the Swabian Jura plateau and its historic textile industry.
  • E. Röthenbach
    Röthenbach is a station in Nuremberg, Germany that serves as a terminus on the city’s U-Bahn rapid transit network.
  • 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_69ad859e529c8190a404273f53cb487d completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb0a2f4708190821edb9700f62d2f completed March 8, 2026, 5:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2f3d759908190b1f5170930ff03c5 completed March 12, 2026, 5:11 p.m.
NEDg Description generation batch_69b2f9ec098c8190aaa763d7b9c5cceb completed March 12, 2026, 5:37 p.m.
NED2 Entity disambiguation (via description) batch_69b316408090819090a4792b3d5185f0 completed March 12, 2026, 7:38 p.m.
Created at: March 8, 2026, 3:10 p.m.