Triple

T2841429
Position Surface form Disambiguated ID Type / Status
Subject Bognor Regis E62477 entity
Predicate hasHonorific P2097 FINISHED
Object Regis
Regis is an honorific term historically used in English to denote royal association, particularly in place names granted royal patronage.
 E304581 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: Regis | Statement: [Bognor Regis, hasHonorific, Regis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Regis
Context triple: [Bognor Regis, hasHonorific, Regis]
  • A. Kogod
    Kogod is the business school of American University in Washington, D.C., offering undergraduate and graduate programs in business and management.
  • B. Creighton Hale
    Creighton Hale was an Irish-born American silent film actor known for his boyish looks and roles in early 20th-century dramas and comedies.
  • C. Eldridge
    Eldridge is an English-language surname of Old English origin, borne by various notable individuals across fields such as politics, the arts, and sports.
  • D. Shattuck
    Shattuck is a small town in northwestern Oklahoma known for its historic windmill park and rural, agricultural character.
  • E. Leland
    Leland is a masculine given name of English origin, historically associated with figures such as American industrialist and Stanford University founder Leland Stanford.
  • 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: Regis
Triple: [Bognor Regis, hasHonorific, Regis]
Generated description
Regis is an honorific term historically used in English to denote royal association, particularly in place names granted royal patronage.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Regis
Target entity description: Regis is an honorific term historically used in English to denote royal association, particularly in place names granted royal patronage.
  • A. Kogod
    Kogod is the business school of American University in Washington, D.C., offering undergraduate and graduate programs in business and management.
  • B. Creighton Hale
    Creighton Hale was an Irish-born American silent film actor known for his boyish looks and roles in early 20th-century dramas and comedies.
  • C. Eldridge
    Eldridge is an English-language surname of Old English origin, borne by various notable individuals across fields such as politics, the arts, and sports.
  • D. Shattuck
    Shattuck is a small town in northwestern Oklahoma known for its historic windmill park and rural, agricultural character.
  • E. Leland
    Leland is a masculine given name of English origin, historically associated with figures such as American industrialist and Stanford University founder Leland Stanford.
  • 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_69ab4c3d16bc81908b3a1c98fbd287fe completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdf16d0c08190bb8de4a4160b4414 completed March 7, 2026, 8:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69afe8d22e588190b119e7d9f9c3873a completed March 10, 2026, 9:48 a.m.
NEDg Description generation batch_69afea1732b481909a8df01d80ca1bd4 completed March 10, 2026, 9:53 a.m.
NED2 Entity disambiguation (via description) batch_69b00eff94b481909a4cc08c8494870c completed March 10, 2026, 12:30 p.m.
Created at: March 6, 2026, 10:01 p.m.