Triple

T16592408
Position Surface form Disambiguated ID Type / Status
Subject Antoinette Amalie of Brunswick-Wolfenbüttel E403121 entity
Predicate givenName P17 FINISHED
Object Amalie
Amalie is a given name associated here with Antoinette Amalie of Brunswick-Wolfenbüttel, a German noblewoman from the House of Brunswick.
 E1222539 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: Amalie | Statement: [Antoinette Amalie of Brunswick-Wolfenbüttel, givenName, Amalie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Amalie
Context triple: [Antoinette Amalie of Brunswick-Wolfenbüttel, givenName, Amalie]
  • A. Amalie
    Amalie is a motor oil and lubricants brand known for producing automotive and industrial oils.
  • B. Amalie
    Amalie is a given name associated with Princess Marianne of Prussia, a 19th-century Prussian royal.
  • C. Amalie
    Amalie is the given first name of the pioneering German mathematician Emmy Noether, renowned for her foundational contributions to abstract algebra and theoretical physics.
  • D. Amalia
    Amalia is a novel by Finnish writer Sylvi Kekkonen, known for its introspective portrayal of women’s inner lives in mid-20th-century Finland.
  • E. Amalia
    Amalia is a character in Mario Vargas Llosa’s novel "Conversación en La Catedral," representing one of the many figures entangled in the political and social decay of mid-20th-century Peru.
  • 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: Amalie
Triple: [Antoinette Amalie of Brunswick-Wolfenbüttel, givenName, Amalie]
Generated description
Amalie is a given name associated here with Antoinette Amalie of Brunswick-Wolfenbüttel, a German noblewoman from the House of Brunswick.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Amalie
Target entity description: Amalie is a given name associated here with Antoinette Amalie of Brunswick-Wolfenbüttel, a German noblewoman from the House of Brunswick.
  • A. Amalie
    Amalie is the given first name of the pioneering German mathematician Emmy Noether, renowned for her foundational contributions to abstract algebra and theoretical physics.
  • B. Amalie
    Amalie is a motor oil and lubricants brand known for producing automotive and industrial oils.
  • C. Amalie
    Amalie is a given name associated with Princess Marianne of Prussia, a 19th-century Prussian royal.
  • D. Amalia
    Amalia is a character in Franz Kafka’s unfinished novel "The Castle," known for her defiant act that brings social ostracism upon her family.
  • E. Amalia
    Amalia is a novel by Finnish writer Sylvi Kekkonen, known for its introspective portrayal of women’s inner lives in mid-20th-century Finland.
  • 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_69d88387363c8190a97a0c942130de97 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e359a123e8819095cd73cd848a3345 completed April 18, 2026, 10:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00759b9e5081909815d2cd00d44490 completed May 10, 2026, 12:10 p.m.
NEDg Description generation batch_6a007680bc7c81908c81ad690035ed47 completed May 10, 2026, 12:13 p.m.
NED2 Entity disambiguation (via description) batch_6a007728680c819082a3bd7e84edb2b0 completed May 10, 2026, 12:16 p.m.
Created at: April 10, 2026, 5:16 a.m.