Triple

T31490163

Position	Surface form	Disambiguated ID	Type / Status
Subject	Berghof sanatorium	`E803384`	entity
Predicate	staffCharacter	`P93957`	FINISHED
Object	Hofrat Behrens Hofrat Behrens is a fictional senior physician at the Berghof tuberculosis sanatorium in Thomas Mann’s novel "The Magic Mountain," known for his eccentric manner and pivotal role in the lives of the patients.	`E1967470`	NE FINISHED

How this triple was built (3 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: Hofrat Behrens | Statement: [Berghof sanatorium, staffCharacter, Hofrat Behrens]

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: Hofrat Behrens
Triple: [Berghof sanatorium, staffCharacter, Hofrat Behrens]

Generated description

Hofrat Behrens is a fictional senior physician at the Berghof tuberculosis sanatorium in Thomas Mann’s novel "The Magic Mountain," known for his eccentric manner and pivotal role in the lives of the patients.

PD Predicate disambiguation gpt-5-mini-2025-08-07

Target predicate: staffCharacter
Context triple: [Berghof sanatorium, staffCharacter, Hofrat Behrens]

A. storyCharacterizedAs
Indicates that a story is described, portrayed, or defined as having a particular quality, style, or attribute.
B. featuresCharacterRole
Indicates that a work includes a character appearing in a specific narrative or functional role.
C. featuresCharacterWith chosen
Indicates that one entity (such as a work or product) includes or presents a particular character as part of its content.
D. metCharacter
Indicates that one entity has encountered or been introduced to another entity at least once.
E. studentCharacter
Indicates that one entity has the role or qualities of a student in relation to another entity, typically within an educational or learning context.
F. None of above.

Provenance (6 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_69f348ca04508190ba9379b5329dfd75`	completed	April 30, 2026, 12:19 p.m.
NER	Named-entity recognition	`batch_69f6a1e4ca4881908146cb7b170209d6`	completed	May 3, 2026, 1:16 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a2b2d7561688190a1c46ca4c0a5e6f8`	completed	June 11, 2026, 9:49 p.m.
NEDg	Description generation	`batch_6a2b31290c388190bd7d4a9762fa82c6`	completed	June 11, 2026, 10:05 p.m.
NED2	Entity disambiguation (via description)	`batch_6a2b3232bba08190a23e64699f370fbb`	completed	June 11, 2026, 10:09 p.m.
PD	Predicate disambiguation	`batch_69f69fe82e5c81909da9db0a2f3bba6d`	completed	May 3, 2026, 1:07 a.m.

Created at: April 30, 2026, 9:37 p.m.