Triple

T6427243
Position Surface form Disambiguated ID Type / Status
Subject The Black Room E128089 entity
Predicate featuresCharacter P626 FINISHED
Object Gregor de Berghmann
Gregor de Berghmann is a fictional character appearing in the narrative of "The Black Room."
 E594752 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: Gregor de Berghmann | Statement: [The Black Room, featuresCharacter, Gregor de Berghmann]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gregor de Berghmann
Context triple: [The Black Room, featuresCharacter, Gregor de Berghmann]
  • A. Josef Jennewein
    Josef Jennewein was a German World War II Luftwaffe fighter ace and former Olympic alpine skier.
  • B. Ludwig Jekels
    Ludwig Jekels was an Austrian physician and early psychoanalyst who was among the first followers of Sigmund Freud and a contributor to the development and spread of psychoanalytic theory.
  • C. Othmar
    Othmar is a masculine given name of Germanic origin, notably borne by the Swiss-American civil engineer Othmar Ammann.
  • D. Carl Hilpert
    Carl Hilpert was a German Wehrmacht general during World War II who held several high-level commands on the Eastern Front.
  • E. Hermann Blankenstein
    Hermann Blankenstein was a prominent 19th-century German architect best known for designing numerous public buildings in Berlin, particularly schools and administrative structures.
  • 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: Gregor de Berghmann
Triple: [The Black Room, featuresCharacter, Gregor de Berghmann]
Generated description
Gregor de Berghmann is a fictional character appearing in the narrative of "The Black Room."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gregor de Berghmann
Target entity description: Gregor de Berghmann is a fictional character appearing in the narrative of "The Black Room."
  • A. Josef Jennewein
    Josef Jennewein was a German World War II Luftwaffe fighter ace and former Olympic alpine skier.
  • B. Ludwig Jekels
    Ludwig Jekels was an Austrian physician and early psychoanalyst who was among the first followers of Sigmund Freud and a contributor to the development and spread of psychoanalytic theory.
  • C. Othmar
    Othmar is a masculine given name of Germanic origin, notably borne by the Swiss-American civil engineer Othmar Ammann.
  • D. Carl Hilpert
    Carl Hilpert was a German Wehrmacht general during World War II who held several high-level commands on the Eastern Front.
  • E. Hermann Blankenstein
    Hermann Blankenstein was a prominent 19th-century German architect best known for designing numerous public buildings in Berlin, particularly schools and administrative structures.
  • 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_69c00838de888190af2eec0b80495efa completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c06920cef48190a884df8f12987a0d completed March 22, 2026, 10:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69c64bbc865c81909bf064b9253bc263 completed March 27, 2026, 9:19 a.m.
NEDg Description generation batch_69c64e180f948190bbe69467c47c84e3 completed March 27, 2026, 9:30 a.m.
NED2 Entity disambiguation (via description) batch_69c64ead9b8c81908ba74c90057981a6 completed March 27, 2026, 9:32 a.m.
Created at: March 22, 2026, 4:44 p.m.