Triple

T16479797
Position Surface form Disambiguated ID Type / Status
Subject Breisgau-Hochschwarzwald E400283 entity
Predicate contains P35 FINISHED
Object Sulzburg
Sulzburg is a small historic town in southwestern Germany’s Baden-Württemberg region, known for its picturesque setting near the Black Forest and its well-preserved old town.
 E1258201 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: Sulzburg | Statement: [Breisgau-Hochschwarzwald, contains, Sulzburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sulzburg
Context triple: [Breisgau-Hochschwarzwald, contains, Sulzburg]
  • A. Kaufbeuren
    Kaufbeuren is a historic Bavarian town in southern Germany known for its well-preserved medieval old town and traditional Swabian culture.
  • B. Straubing
    Straubing is a Bavarian town on the Danube River known for its historic city center and role as a regional economic and educational hub.
  • C. Schweinfurt
    Schweinfurt is a city in northern Bavaria, Germany, historically known for its ball bearing industry and as a strategic target during World War II.
  • D. Rosenheim
    Rosenheim is a town in Upper Bavaria, Germany, known as a regional economic and transportation hub near the Alps.
  • E. Günzburg
    Günzburg is a small Bavarian town in southern Germany, historically notable as the birthplace of Nazi physician Josef Mengele.
  • 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: Sulzburg
Triple: [Breisgau-Hochschwarzwald, contains, Sulzburg]
Generated description
Sulzburg is a small historic town in southwestern Germany’s Baden-Württemberg region, known for its picturesque setting near the Black Forest and its well-preserved old town.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sulzburg
Target entity description: Sulzburg is a small historic town in southwestern Germany’s Baden-Württemberg region, known for its picturesque setting near the Black Forest and its well-preserved old town.
  • A. Kaufbeuren
    Kaufbeuren is a historic Bavarian town in southern Germany known for its well-preserved medieval old town and traditional Swabian culture.
  • B. Straubing
    Straubing is a Bavarian town on the Danube River known for its historic city center and role as a regional economic and educational hub.
  • C. Schweinfurt
    Schweinfurt is a city in northern Bavaria, Germany, historically known for its ball bearing industry and as a strategic target during World War II.
  • D. Rosenheim
    Rosenheim is a town in Upper Bavaria, Germany, known as a regional economic and transportation hub near the Alps.
  • E. Günzburg
    Günzburg is a small Bavarian town in southern Germany, historically notable as the birthplace of Nazi physician Josef Mengele.
  • 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_69d883813098819084f5409539723b59 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32e01f6c88190b75a0d6c94786426 completed April 18, 2026, 7:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01673979608190905afae3071413c0 completed May 11, 2026, 5:20 a.m.
NEDg Description generation batch_6a016b8609dc8190bfd3e1b6ff715d65 completed May 11, 2026, 5:39 a.m.
NED2 Entity disambiguation (via description) batch_6a016c5018e48190974c124c3433bcc6 completed May 11, 2026, 5:42 a.m.
Created at: April 10, 2026, 5:13 a.m.