Triple

T22258525
Position Surface form Disambiguated ID Type / Status
Subject John Tallis E550154 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 Tallis, givenName, John]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John
Context triple: [John Tallis, givenName, John]
  • A. John
    John is the given name of John Cockcroft, a pioneering British physicist and Nobel laureate known for his work on nuclear physics and particle acceleration.
  • B. John
    John is the given name of John J. Pershing, the famed American general who led the American Expeditionary Forces in World War I.
  • C. John
    John is the given name of John W. Mauchly, the American physicist and co-inventor of the ENIAC computer.
  • D. John
    John is the given first name of Johnny Kilbane, an American featherweight boxing champion from the early 20th century.
  • E. John
    John is the given name of John Albert William Spencer-Churchill, a British aristocrat and 10th Duke of Marlborough.
  • 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 Tallis, 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 John Graunt, a 17th-century English statistician and demographer known for pioneering work in population statistics.
  • D. John
    John is the given name of the influential English philosopher John Locke, a key figure in empiricism and liberal political theory.
  • E. 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.
  • 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_69e11e42adb8819087714772ea606709 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f138c4bff48190b4be83f5f7677ac8 completed April 28, 2026, 10:46 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0ab662334c819095b6737e550bd5ce completed May 18, 2026, 6:49 a.m.
NEDg Description generation batch_6a0ab77252b0819098e9daa2930ceb6a completed May 18, 2026, 6:53 a.m.
NED2 Entity disambiguation (via description) batch_6a0ab81e47a08190b4148080f363fcf5 completed May 18, 2026, 6:56 a.m.
Created at: April 16, 2026, 8:39 p.m.