Triple

T10349015
Position Surface form Disambiguated ID Type / Status
Subject Außenalster E243829 entity
Predicate borderedBy P224 FINISHED
Object Uhlenhorst
Uhlenhorst is a well-to-do residential and cultural district in Hamburg, Germany, known for its waterfront location, historic villas, and proximity to the Alster lakes.
 E857770 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: Uhlenhorst | Statement: [Außenalster, borderedBy, Uhlenhorst]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Uhlenhorst
Context triple: [Außenalster, borderedBy, Uhlenhorst]
  • A. Neebe
    Neebe is a surname most notably associated with Oscar Neebe, an American labor activist and one of the defendants in the 1886 Haymarket affair.
  • B. Fitz Hugh Sound
    Fitz Hugh Sound is a coastal waterway on the central coast of British Columbia, Canada, known for its rich marine ecosystems and significance within Indigenous Heiltsuk territory.
  • C. Arrott
    Arrott is the station code for the Arrott Transportation Center, a public transit hub in Philadelphia, Pennsylvania.
  • D. Ottenstein
    Ottenstein is a district (Ortsteil) of the town of Ahaus in the state of North Rhine-Westphalia, Germany.
  • E. Fontan
    Fontan is a fictional character named Nana Fontan, likely appearing in a narrative work such as a novel, film, or television series.
  • 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: Uhlenhorst
Triple: [Außenalster, borderedBy, Uhlenhorst]
Generated description
Uhlenhorst is a well-to-do residential and cultural district in Hamburg, Germany, known for its waterfront location, historic villas, and proximity to the Alster lakes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Uhlenhorst
Target entity description: Uhlenhorst is a well-to-do residential and cultural district in Hamburg, Germany, known for its waterfront location, historic villas, and proximity to the Alster lakes.
  • A. Neebe
    Neebe is a surname most notably associated with Oscar Neebe, an American labor activist and one of the defendants in the 1886 Haymarket affair.
  • B. Fitz Hugh Sound
    Fitz Hugh Sound is a coastal waterway on the central coast of British Columbia, Canada, known for its rich marine ecosystems and significance within Indigenous Heiltsuk territory.
  • C. Arrott
    Arrott is the station code for the Arrott Transportation Center, a public transit hub in Philadelphia, Pennsylvania.
  • D. Ottenstein
    Ottenstein is a district (Ortsteil) of the town of Ahaus in the state of North Rhine-Westphalia, Germany.
  • E. Fontan
    Fontan is a fictional character named Nana Fontan, likely appearing in a narrative work such as a novel, film, or television series.
  • 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_69d381b22b8c8190aaed476be5f872a9 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e946cbb881909b88536d0107995d completed April 7, 2026, 11:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69d7508e325c8190a88c2b972f8a6846 completed April 9, 2026, 7:09 a.m.
NEDg Description generation batch_69d7618da0188190901026dd51ceaa46 completed April 9, 2026, 8:21 a.m.
NED2 Entity disambiguation (via description) batch_69d77045ea988190bd8e31f5f636f69b completed April 9, 2026, 9:24 a.m.
Created at: April 6, 2026, 11:57 a.m.