Triple

T20880062
Position Surface form Disambiguated ID Type / Status
Subject John Coffee Hays E514120 entity
Predicate givenName P17 FINISHED
Object John
John is the given name of John Coffee Hays, a famed 19th-century Texas Ranger and military officer in the United States.
E1457273 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 Coffee Hays, givenName, John]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John
Context triple: [John Coffee Hays, givenName, John]
  • A. John
    John is the given first name of Johnny Kilbane, an American featherweight boxing champion from the early 20th century.
  • B. John
    John is the given name of John Albert William Spencer-Churchill, a British aristocrat and 10th Duke of Marlborough.
  • C. John
    John is the middle name of Samuel John Mills, an American Congregationalist minister known for his role in early 19th-century missionary movements.
  • D. John
    John is the given first name of Australian actor Chips Rafferty, a prominent figure in mid-20th-century Australian cinema.
  • E. John
    John is the given name of John Romita Sr., the influential American comic book artist best known for his work on Marvel's The Amazing Spider-Man.
  • 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 Coffee Hays, givenName, John]
Generated description
John is the given name of John Coffee Hays, a famed 19th-century Texas Ranger and military officer in the United States.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: John
Target entity description: John is the given name of John Coffee Hays, a famed 19th-century Texas Ranger and military officer in the United States.
  • A. John
    John is the given name of John H. Reagan, a prominent 19th-century American politician who served as a Confederate postmaster general and later as a U.S. congressman and senator from Texas.
  • B. John
    John is the given name of John E. Wool, a prominent 19th-century United States Army officer and Mexican–American War general.
  • C. John
    John is the given name of John Bell Hood, a Confederate general known for his aggressive command during the American Civil War.
  • D. John
    John is the given name of John Alexander Logan, a prominent 19th-century American Civil War general and influential politician.
  • E. John
    John is the given name of John F. Reynolds, a Union Army general who served during the American Civil War.
  • 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_69e0b4f733f081908a401c0b7beb0b9f completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c67974348190bd3484032c0d7b31 completed April 21, 2026, 12:36 a.m.
NED1 Entity disambiguation (via context triple) batch_6a091fb7de50819098e0ef8299156950 completed May 17, 2026, 1:54 a.m.
NEDg Description generation batch_6a092016cc588190a41a0f05cc2afbb4 completed May 17, 2026, 1:55 a.m.
NED2 Entity disambiguation (via description) batch_6a0920b3dfac8190a12229c81663b324 completed May 17, 2026, 1:58 a.m.
Created at: April 16, 2026, 12:45 p.m.