Triple

T8897753
Position Surface form Disambiguated ID Type / Status
Subject King Ban of Benwick E211847 entity
Predicate realm P12844 FINISHED
Object Benoic
Benoic is a legendary Arthurian kingdom traditionally associated with King Ban and often linked to the region of Benwick in medieval romance literature.
 E764928 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: Benoic | Statement: [King Ban of Benwick, realm, Benoic]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Benoic
Context triple: [King Ban of Benwick, realm, Benoic]
  • A. Beno
    Beno is the given name of the German seismologist Beno Gutenberg, known for his pioneering work on the structure of the Earth's interior.
  • B. BEN
    BEN is the three-letter IATA airport code assigned to Benina International Airport serving Benghazi, Libya.
  • C. Benso
    Benso is the aristocratic family name of Camillo Benso, Count of Cavour, a leading statesman of the Italian unification.
  • D. Benetutti
    Benetutti is a small town and comune in the province of Sassari in Sardinia, Italy, known for its thermal springs and location within the historical region of Logudoro.
  • E. BON
    BON is the National Rail station code for Bolton railway station in Greater Manchester, England.
  • 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: Benoic
Triple: [King Ban of Benwick, realm, Benoic]
Generated description
Benoic is a legendary Arthurian kingdom traditionally associated with King Ban and often linked to the region of Benwick in medieval romance literature.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Benoic
Target entity description: Benoic is a legendary Arthurian kingdom traditionally associated with King Ban and often linked to the region of Benwick in medieval romance literature.
  • A. Beno
    Beno is the given name of the German seismologist Beno Gutenberg, known for his pioneering work on the structure of the Earth's interior.
  • B. BEN
    BEN is the three-letter IATA airport code assigned to Benina International Airport serving Benghazi, Libya.
  • C. Benso
    Benso is the aristocratic family name of Camillo Benso, Count of Cavour, a leading statesman of the Italian unification.
  • D. Benetutti
    Benetutti is a small town and comune in the province of Sassari in Sardinia, Italy, known for its thermal springs and location within the historical region of Logudoro.
  • E. BON
    BON is the National Rail station code for Bolton railway station in Greater Manchester, England.
  • 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_69ca83918d3081909b326fa3750cb8c8 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6424a8c08190aef2aa2079dd85f1 completed April 1, 2026, 12:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfac093034819085d8fb1832ec5d73 completed April 3, 2026, 12:01 p.m.
NEDg Description generation batch_69cfacb58f208190b5e8eeba58f1bd78 completed April 3, 2026, 12:04 p.m.
NED2 Entity disambiguation (via description) batch_69cfad6fff348190b0491ba38d2e6ce5 completed April 3, 2026, 12:07 p.m.
Created at: March 30, 2026, 6:54 p.m.