Triple

T7979871
Position Surface form Disambiguated ID Type / Status
Subject Bernicia E185543 entity
Predicate alternativeName P39 FINISHED
Object Beornice
Beornice is an alternative historical name for Bernicia, an early medieval Anglo-Saxon kingdom in what is now northern England and southeastern Scotland.
 E705197 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: Beornice | Statement: [Bernicia, alternativeName, Beornice]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Beornice
Context triple: [Bernicia, alternativeName, Beornice]
  • A. Borbera
    Borbera is a river in northwestern Italy that flows through the Piedmont region before joining the Tanaro.
  • B. Borzna
    Borzna is a historic town in northern Ukraine, known as a former regional center within various administrative divisions over the centuries.
  • C. Börje
    Börje is a masculine given name of Swedish origin, notably borne by the legendary ice hockey player Börje Salming.
  • D. Orzola
    Orzola is a small fishing village and port at the northern tip of Lanzarote in the Canary Islands, known as the main departure point for ferries to the nearby island of La Graciosa.
  • E. Velda
    Velda is the loyal and resourceful secretary and love interest of private investigator Mike Hammer in the hardboiled crime novel and film "Kiss Me Deadly."
  • 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: Beornice
Triple: [Bernicia, alternativeName, Beornice]
Generated description
Beornice is an alternative historical name for Bernicia, an early medieval Anglo-Saxon kingdom in what is now northern England and southeastern Scotland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Beornice
Target entity description: Beornice is an alternative historical name for Bernicia, an early medieval Anglo-Saxon kingdom in what is now northern England and southeastern Scotland.
  • A. Borbera
    Borbera is a river in northwestern Italy that flows through the Piedmont region before joining the Tanaro.
  • B. Borzna
    Borzna is a historic town in northern Ukraine, known as a former regional center within various administrative divisions over the centuries.
  • C. Börje
    Börje is a masculine given name of Swedish origin, notably borne by the legendary ice hockey player Börje Salming.
  • D. Orzola
    Orzola is a small fishing village and port at the northern tip of Lanzarote in the Canary Islands, known as the main departure point for ferries to the nearby island of La Graciosa.
  • E. Velda
    Velda is the loyal and resourceful secretary and love interest of private investigator Mike Hammer in the hardboiled crime novel and film "Kiss Me Deadly."
  • 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_69ca829851908190b4e03829353ee7c3 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3c261904819086910898071f3629 completed March 31, 2026, 3:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69cbe0d3c724819087df03cea2ed998f completed March 31, 2026, 2:57 p.m.
NEDg Description generation batch_69cc46c221848190848c7e017e532a16 completed March 31, 2026, 10:12 p.m.
NED2 Entity disambiguation (via description) batch_69cc480d2f40819085046a1d0c9d05e0 completed March 31, 2026, 10:17 p.m.
Created at: March 30, 2026, 5:14 p.m.