Triple

T14755448
Position Surface form Disambiguated ID Type / Status
Subject Graben (street) E346717 entity
Predicate hasPart P35 FINISHED
Object Grabenhof
Grabenhof is a notable building complex located on Vienna’s historic Graben street, known for its characteristic 19th-century architecture and prominent city-center location.
E1117265 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: Grabenhof | Statement: [Graben (street), hasPart, Grabenhof]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grabenhof
Context triple: [Graben (street), hasPart, Grabenhof]
  • A. Schickenhof
    Schickenhof is a small locality in Germany best known as the birthplace of Nobel Prize–winning physicist Johannes Stark.
  • B. Marienhof
    Marienhof is a German television soap opera that gained popularity in the 1990s and 2000s for its portrayal of everyday life and relationships in a fictional Cologne neighborhood.
  • C. Hartmannshof
    Hartmannshof is a locality in Bavaria, Germany, that functions as an outer terminus on the Nuremberg S-Bahn commuter rail network.
  • D. Samenhof
    Samenhof is a surname most notably associated with L. L. Zamenhof, the creator of the constructed international language Esperanto.
  • E. Scheibenhof
    Scheibenhof is a locality or district that forms part of the city of Krems an der Donau in Lower Austria.
  • 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: Grabenhof
Triple: [Graben (street), hasPart, Grabenhof]
Generated description
Grabenhof is a notable building complex located on Vienna’s historic Graben street, known for its characteristic 19th-century architecture and prominent city-center location.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Grabenhof
Target entity description: Grabenhof is a notable building complex located on Vienna’s historic Graben street, known for its characteristic 19th-century architecture and prominent city-center location.
  • A. Schickenhof
    Schickenhof is a small locality in Germany best known as the birthplace of Nobel Prize–winning physicist Johannes Stark.
  • B. Marienhof
    Marienhof is a German television soap opera that gained popularity in the 1990s and 2000s for its portrayal of everyday life and relationships in a fictional Cologne neighborhood.
  • C. Hartmannshof
    Hartmannshof is a locality in Bavaria, Germany, that functions as an outer terminus on the Nuremberg S-Bahn commuter rail network.
  • D. Samenhof
    Samenhof is a surname most notably associated with L. L. Zamenhof, the creator of the constructed international language Esperanto.
  • E. Scheibenhof
    Scheibenhof is a locality or district that forms part of the city of Krems an der Donau in Lower Austria.
  • 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_69d822e8896c819091169882f9b20486 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec7ef0fd48190bd4a8af128ef274c completed April 14, 2026, 11:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdfb9e1b8481909abea3daabe91302 completed May 8, 2026, 3:05 p.m.
NEDg Description generation batch_69fdfe5f00b08190ba44acd2eed94333 completed May 8, 2026, 3:16 p.m.
NED2 Entity disambiguation (via description) batch_69fdff32e0a48190acc14ceccea3df17 completed May 8, 2026, 3:20 p.m.
Created at: April 10, 2026, 1:30 a.m.