Triple

T12385505
Position Surface form Disambiguated ID Type / Status
Subject Erlangen-Höchstadt E295851 entity
Predicate containsMunicipality P852 FINISHED
Object Heroldsberg
Heroldsberg is a municipality in the Erlangen-Höchstadt district of Bavaria, Germany, known for its historic center and proximity to the city of Nuremberg.
E1011607 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: Heroldsberg | Statement: [Erlangen-Höchstadt, containsMunicipality, Heroldsberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Heroldsberg
Context triple: [Erlangen-Höchstadt, containsMunicipality, Heroldsberg]
  • A. 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.
  • B. Schramberg
    Schramberg is a town in the Black Forest region of Baden-Württemberg, Germany, known for its historic clockmaking industry and picturesque valley setting.
  • C. Geisenheim
    Geisenheim is a German town in the Rheingau wine region, known for its viticulture, wine production, and renowned university of applied sciences for wine and horticulture.
  • D. Sporkenheim
    Sporkenheim is a district or locality within the town of Ingelheim am Rhein in Rhineland-Palatinate, Germany.
  • E. Holthausen
    Holthausen is a district of the German town of Hattingen in North Rhine-Westphalia.
  • 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: Heroldsberg
Triple: [Erlangen-Höchstadt, containsMunicipality, Heroldsberg]
Generated description
Heroldsberg is a municipality in the Erlangen-Höchstadt district of Bavaria, Germany, known for its historic center and proximity to the city of Nuremberg.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Heroldsberg
Target entity description: Heroldsberg is a municipality in the Erlangen-Höchstadt district of Bavaria, Germany, known for its historic center and proximity to the city of Nuremberg.
  • A. 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.
  • B. Schramberg
    Schramberg is a town in the Black Forest region of Baden-Württemberg, Germany, known for its historic clockmaking industry and picturesque valley setting.
  • C. Geisenheim
    Geisenheim is a German town in the Rheingau wine region, known for its viticulture, wine production, and renowned university of applied sciences for wine and horticulture.
  • D. Sporkenheim
    Sporkenheim is a district or locality within the town of Ingelheim am Rhein in Rhineland-Palatinate, Germany.
  • E. Holthausen
    Holthausen is a district of the German town of Hattingen in North Rhine-Westphalia.
  • 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_69d6ad9e653c8190b1473c860ee53dae completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d93fbd489c819098233a111442762e completed April 10, 2026, 6:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6af41f6b88190ba3a0b4d531853d7 completed May 3, 2026, 2:13 a.m.
NEDg Description generation batch_69f6b0653ef88190ad0e3a48675ecdcc completed May 3, 2026, 2:18 a.m.
NED2 Entity disambiguation (via description) batch_69f6b1a539148190be7a4f16f738ca90 completed May 3, 2026, 2:23 a.m.
Created at: April 8, 2026, 9:54 p.m.