Triple

T2315486
Position Surface form Disambiguated ID Type / Status
Subject Eastern Sudanic languages E51052 entity
Predicate hasNotableLanguage P7390 FINISHED
Object Berta
Berta is a Nilo-Saharan language spoken primarily in parts of Sudan and Ethiopia.
 E255792 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: Berta | Statement: [Eastern Sudanic languages, hasNotableLanguage, Berta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Berta
Context triple: [Eastern Sudanic languages, hasNotableLanguage, Berta]
  • A. Berta
    Berta is a fictional character in Paulo Coelho’s novel "The Devil and Miss Prym," serving as one of the villagers whose life and choices reflect the book’s central moral and spiritual dilemmas.
  • B. Bubi
    Bubi is a Bantu language spoken by the Bubi people, primarily on Bioko Island in Equatorial Guinea.
  • C. Bubi
    Bubi is the nickname of Erich Hartmann, the German World War II fighter pilot who became history’s highest-scoring flying ace.
  • D. Wilhelma
    Wilhelma is a renowned zoological and botanical garden in Stuttgart, Germany, known for its extensive animal and plant collections and historic Moorish-style architecture.
  • E. Zibelle
    Zibelle is a village in eastern Germany, historically part of Lusatia, known in this context as the place where physicist Walther Nernst died.
  • 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: Berta
Triple: [Eastern Sudanic languages, hasNotableLanguage, Berta]
Generated description
Berta is a Nilo-Saharan language spoken primarily in parts of Sudan and Ethiopia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Berta
Target entity description: Berta is a Nilo-Saharan language spoken primarily in parts of Sudan and Ethiopia.
  • A. Berta
    Berta is a fictional character in Paulo Coelho’s novel "The Devil and Miss Prym," serving as one of the villagers whose life and choices reflect the book’s central moral and spiritual dilemmas.
  • B. Bubi
    Bubi is the nickname of Erich Hartmann, the German World War II fighter pilot who became history’s highest-scoring flying ace.
  • C. Bubi
    Bubi is a Bantu language spoken by the Bubi people, primarily on Bioko Island in Equatorial Guinea.
  • D. Wilhelma
    Wilhelma is a renowned zoological and botanical garden in Stuttgart, Germany, known for its extensive animal and plant collections and historic Moorish-style architecture.
  • E. Zibelle
    Zibelle is a village in eastern Germany, historically part of Lusatia, known in this context as the place where physicist Walther Nernst died.
  • 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_69a88b074b908190ae983dbca7757d88 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc61e72508190b335cda2c7fef130 completed March 7, 2026, 6:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae896236f08190b3874854279bbdf7 completed March 9, 2026, 8:48 a.m.
NEDg Description generation batch_69ae8b0b27cc819099a5df60d678d3e2 completed March 9, 2026, 8:55 a.m.
NED2 Entity disambiguation (via description) batch_69ae8b79633881908acf94f8db389c0f completed March 9, 2026, 8:57 a.m.
Created at: March 4, 2026, 7:49 p.m.