Triple

T15473608
Position Surface form Disambiguated ID Type / Status
Subject Böblingen district E376726 entity
Predicate containsMunicipality P852 FINISHED
Object Deckenpfronn
Deckenpfronn is a small municipality in the German state of Baden-Württemberg, situated in the Böblingen district near the northern edge of the Black Forest.
E1159149 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: Deckenpfronn | Statement: [Böblingen district, containsMunicipality, Deckenpfronn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Deckenpfronn
Context triple: [Böblingen district, containsMunicipality, Deckenpfronn]
  • A. Himmelbett
    Himmelbett was a German World War II night air defense system that coordinated radar, searchlights, and fighter aircraft to intercept Allied bombers.
  • B. Tiège
    Tiège is a village in the municipality of Jalhay in the province of Liège, Belgium.
  • C. Unterdießen
    Unterdießen is a small municipality in the district of Landsberg am Lech in Bavaria, Germany.
  • D. Nordecke
    Nordecke is the passionate supporters’ section of Major League Soccer club Columbus Crew, known for its loud atmosphere, coordinated chants, and vibrant matchday displays.
  • E. Knuffingen
    Knuffingen is a fictional miniature city featured in Hamburg’s Miniatur Wunderland, known for its detailed urban landscape and automated model railway and traffic systems.
  • 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: Deckenpfronn
Triple: [Böblingen district, containsMunicipality, Deckenpfronn]
Generated description
Deckenpfronn is a small municipality in the German state of Baden-Württemberg, situated in the Böblingen district near the northern edge of the Black Forest.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Deckenpfronn
Target entity description: Deckenpfronn is a small municipality in the German state of Baden-Württemberg, situated in the Böblingen district near the northern edge of the Black Forest.
  • A. Himmelbett
    Himmelbett was a German World War II night air defense system that coordinated radar, searchlights, and fighter aircraft to intercept Allied bombers.
  • B. Tiège
    Tiège is a village in the municipality of Jalhay in the province of Liège, Belgium.
  • C. Unterdießen
    Unterdießen is a small municipality in the district of Landsberg am Lech in Bavaria, Germany.
  • D. Nordecke
    Nordecke is the passionate supporters’ section of Major League Soccer club Columbus Crew, known for its loud atmosphere, coordinated chants, and vibrant matchday displays.
  • E. Knuffingen
    Knuffingen is a fictional miniature city featured in Hamburg’s Miniatur Wunderland, known for its detailed urban landscape and automated model railway and traffic systems.
  • 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_69d85cd21dcc81908646251b1c26ea00 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03f6e859481909c3d08343b7ad27c completed April 16, 2026, 1:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff2d075e64819097061ef4c205577e completed May 9, 2026, 12:48 p.m.
NEDg Description generation batch_69ff2e1fb27c81908de0d755bf30c833 completed May 9, 2026, 12:52 p.m.
NED2 Entity disambiguation (via description) batch_69ff2f3ab6988190b4cefe2f55c4101c completed May 9, 2026, 12:57 p.m.
Created at: April 10, 2026, 3:34 a.m.