Triple

T13255273
Position Surface form Disambiguated ID Type / Status
Subject Kelkheim E315641 entity
Predicate hasSubdivision P747 FINISHED
Object Hornau
Hornau is a district of the town of Kelkheim in the Main-Taunus region of Hesse, Germany.
E1128681 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: Hornau | Statement: [Kelkheim, hasSubdivision, Hornau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hornau
Context triple: [Kelkheim, hasSubdivision, Hornau]
  • A. Hasselwerder
    Hasselwerder is a small island located in Lake Tegel in Berlin, Germany.
  • B. Ehringshausen
    Ehringshausen is a municipality in the Lahn-Dill district of the German state of Hesse.
  • C. Hademstorf
    Hademstorf is a small municipality in Lower Saxony, Germany, situated in the Heidekreis district.
  • D. Göhren
    Göhren is a seaside resort town on the Baltic Sea coast of Germany, located on the island of Rügen and known for its beaches and tourism.
  • E. Meinerzhagen
    Meinerzhagen is a town in western Germany known for its location in the hilly, forested Sauerland region of 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: Hornau
Triple: [Kelkheim, hasSubdivision, Hornau]
Generated description
Hornau is a district of the town of Kelkheim in the Main-Taunus region of Hesse, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Hornau
Target entity description: Hornau is a district of the town of Kelkheim in the Main-Taunus region of Hesse, Germany.
  • A. Hasselwerder
    Hasselwerder is a small island located in Lake Tegel in Berlin, Germany.
  • B. Ehringshausen
    Ehringshausen is a municipality in the Lahn-Dill district of the German state of Hesse.
  • C. Hademstorf
    Hademstorf is a small municipality in Lower Saxony, Germany, situated in the Heidekreis district.
  • D. Göhren
    Göhren is a seaside resort town on the Baltic Sea coast of Germany, located on the island of Rügen and known for its beaches and tourism.
  • E. Meinerzhagen
    Meinerzhagen is a town in western Germany known for its location in the hilly, forested Sauerland region of 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_69d806b1072881909e46bd212259c5f0 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98f7517048190b4eac4e44e81ff66 completed April 11, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe7e70dc788190850278a40a5a62e4 completed May 9, 2026, 12:23 a.m.
NEDg Description generation batch_69fe803875988190a4786db4ae0b0cbb completed May 9, 2026, 12:30 a.m.
NED2 Entity disambiguation (via description) batch_69fe80be100481908dcf07b683fc1411 completed May 9, 2026, 12:33 a.m.
Created at: April 9, 2026, 9:24 p.m.