Triple

T14994627
Position Surface form Disambiguated ID Type / Status
Subject Bremen Roland statue E373923 entity
Predicate alsoKnownAs P39 FINISHED
Object Bremer Roland
Bremer Roland is a famous medieval statue in Bremen, Germany, symbolizing the city’s freedom and market rights.
E1131159 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: Bremer Roland | Statement: [Bremen Roland statue, alsoKnownAs, Bremer Roland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bremer Roland
Context triple: [Bremen Roland statue, alsoKnownAs, Bremer Roland]
  • A. Leiningen
    Leiningen is a popular build automation and project management tool for the Clojure programming language, used to manage dependencies, run tasks, and streamline development workflows.
  • B. Burgard
    Burgard is a German surname borne by individuals such as the computer scientist Wolfram Burgard.
  • C. Heideck
    Heideck was a notable Philhellene, remembered for his support of the Greek cause during the Greek War of Independence.
  • D. Dukenburg
    Dukenburg is a residential district in the southwest of Nijmegen in the Netherlands, known for its post-war urban planning and local railway connectivity.
  • E. Heinrici
    Heinrici is a German surname most notably associated with Gotthard Heinrici, a senior Wehrmacht general during World War II.
  • 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: Bremer Roland
Triple: [Bremen Roland statue, alsoKnownAs, Bremer Roland]
Generated description
Bremer Roland is a famous medieval statue in Bremen, Germany, symbolizing the city’s freedom and market rights.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Bremer Roland
Target entity description: Bremer Roland is a famous medieval statue in Bremen, Germany, symbolizing the city’s freedom and market rights.
  • A. Leiningen
    Leiningen is a popular build automation and project management tool for the Clojure programming language, used to manage dependencies, run tasks, and streamline development workflows.
  • B. Burgard
    Burgard is a German surname borne by individuals such as the computer scientist Wolfram Burgard.
  • C. Heideck
    Heideck was a notable Philhellene, remembered for his support of the Greek cause during the Greek War of Independence.
  • D. Dukenburg
    Dukenburg is a residential district in the southwest of Nijmegen in the Netherlands, known for its post-war urban planning and local railway connectivity.
  • E. Heinrici
    Heinrici is a German surname most notably associated with Gotthard Heinrici, a senior Wehrmacht general during World War II.
  • 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_69d85ccc84388190aa151e5173370c8d completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded716ebb481908224d2d4f7561b03 completed April 15, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe969a63f081908bf11783e2a51229 completed May 9, 2026, 2:06 a.m.
NEDg Description generation batch_69fe97609b3481908ed481f9f061b148 completed May 9, 2026, 2:09 a.m.
NED2 Entity disambiguation (via description) batch_69fe980155748190aef4ce876f985ef2 completed May 9, 2026, 2:12 a.m.
Created at: April 10, 2026, 2:53 a.m.