Triple

T4209983
Position Surface form Disambiguated ID Type / Status
Subject Kerr E93876 entity
Predicate hasNotableBearer P458 FINISHED
Object Michael Kerr
Michael Kerr is a name shared by several notable individuals, including a Canadian NHL defenseman and a British Labour politician who served as Speaker of the House of Commons.
 E421889 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: Michael Kerr | Statement: [Kerr, hasNotableBearer, Michael Kerr]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Michael Kerr
Context triple: [Kerr, hasNotableBearer, Michael Kerr]
  • A. Michael Coulter
    Michael Coulter is a British cinematographer known for his work on popular films including the romantic comedy "Love Actually."
  • B. Mikal Cronin
    Mikal Cronin is an American musician and songwriter known for his melodic, garage rock-influenced indie pop and frequent collaborations with fellow artist Ty Segall.
  • C. Andrew Sharp
    Andrew Sharp is a British business executive and former CEO of the travel company Eurostar.
  • D. Luke Rowan
    Luke Rowan is a fictional character from the works of 19th-century English novelist Anthony Trollope.
  • E. Paul Kelly
    Paul Kelly was an American stage and film actor active in the early to mid-20th century, known for his character roles in numerous Hollywood productions.
  • 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: Michael Kerr
Triple: [Kerr, hasNotableBearer, Michael Kerr]
Generated description
Michael Kerr is a name shared by several notable individuals, including a Canadian NHL defenseman and a British Labour politician who served as Speaker of the House of Commons.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Michael Kerr
Target entity description: Michael Kerr is a name shared by several notable individuals, including a Canadian NHL defenseman and a British Labour politician who served as Speaker of the House of Commons.
  • A. Michael Coulter
    Michael Coulter is a British cinematographer known for his work on popular films including the romantic comedy "Love Actually."
  • B. Mikal Cronin
    Mikal Cronin is an American musician and songwriter known for his melodic, garage rock-influenced indie pop and frequent collaborations with fellow artist Ty Segall.
  • C. Andrew Sharp
    Andrew Sharp is a British business executive and former CEO of the travel company Eurostar.
  • D. Luke Rowan
    Luke Rowan is a fictional character from the works of 19th-century English novelist Anthony Trollope.
  • E. Paul Kelly
    Paul Kelly was an American stage and film actor active in the early to mid-20th century, known for his character roles in numerous Hollywood productions.
  • 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_69b3451743608190808f41d17ccf2650 completed March 12, 2026, 10:58 p.m.
NER Named-entity recognition batch_69b34810de648190b09c5e705cf0a74e completed March 12, 2026, 11:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5962ec4f8819085bef81ce71aa132 completed March 14, 2026, 5:09 p.m.
NEDg Description generation batch_69b596eb6c288190a63c61d5e71c609b completed March 14, 2026, 5:12 p.m.
NED2 Entity disambiguation (via description) batch_69b59788ef308190a34c2f23f22a7e4d completed March 14, 2026, 5:14 p.m.
Created at: March 12, 2026, 11:03 p.m.