Triple

T12141082
Position Surface form Disambiguated ID Type / Status
Subject John Kipling E289183 entity
Predicate givenName P17 FINISHED
Object John
John is a masculine given name of Hebrew origin, widely used in English-speaking countries and borne by numerous historical, religious, and cultural figures.
E55602 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: John | Statement: [John Kipling, givenName, John]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John
Context triple: [John Kipling, givenName, John]
  • A. John
    John is the nickname of John Riggins, a former American football running back best known for his Hall of Fame career with the Washington Redskins in the NFL.
  • B. John
    John is the given name of John Boyd-Carpenter, a prominent British Conservative politician who served in several senior government positions in the mid-20th century.
  • C. John
    John is the first name of John Dashwood, a character in Jane Austen's novel "Sense and Sensibility."
  • D. John
    John is the given first name of American character actor and comedian Rags Ragland.
  • E. John
    John is the first name of the fictional character John Connor, the prophesied leader of the human resistance in the Terminator franchise.
  • 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: John
Triple: [John Kipling, givenName, John]
Generated description
John is a masculine given name of Hebrew origin, widely used in English-speaking countries and borne by numerous historical, religious, and cultural figures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: John
Target entity description: John is a masculine given name of Hebrew origin, widely used in English-speaking countries and borne by numerous historical, religious, and cultural figures.
  • A. John chosen
    John is a masculine given name of Hebrew origin, widely used in English-speaking countries and borne by numerous historical and contemporary figures.
  • B. John
    John is a common English surname borne by numerous individuals across various fields and cultures.
  • C. John
    John is the given name of the influential English philosopher John Locke, a key figure in empiricism and liberal political theory.
  • D. John
    John is the given name of John Houseman, the Romanian-born British-American actor and producer known for his work in film, theater, and radio.
  • E. John
    John is the given name of John Lennon, the iconic English singer-songwriter and co-founder of The Beatles.
  • F. None of above.

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_69d6ab4c6710819097a9d228382dde43 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d915a9838081909622cc14df2a2582 completed April 10, 2026, 3:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f642801881909a94d67c99bfd110 completed May 2, 2026, 1:04 p.m.
NEDg Description generation batch_69f5fdebe3fc81909a5bb23a943c3c43 completed May 2, 2026, 1:36 p.m.
NED2 Entity disambiguation (via description) batch_69f5feeaf2e48190995f282b02a9caaf completed May 2, 2026, 1:40 p.m.
Created at: April 8, 2026, 9:49 p.m.