Triple

T20116493
Position Surface form Disambiguated ID Type / Status
Subject Thomas Francis Dorsey Jr. E490475 entity
Predicate givenName P17 FINISHED
Object Thomas
Thomas is a masculine given name of Aramaic origin, widely used in English-speaking countries and historically associated with Christian and Western cultural traditions.
E67625 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: Thomas | Statement: [Thomas Francis Dorsey Jr., givenName, Thomas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Thomas
Context triple: [Thomas Francis Dorsey Jr., givenName, Thomas]
  • A. Thomas
    Thomas is the given name of Sir Stamford Raffles, the British statesman best known as the founder of modern Singapore.
  • B. Thomas
    Thomas is the middle name of the individual Samuel Thomas Wilson.
  • C. Thomas
    Thomas is the given name of Thomas Coke, 2nd Earl of Leicester, a prominent 19th-century British peer and landowner.
  • D. Thomas
    Thomas is the full given name of former NFL quarterback Tommy Maddox, who notably played for the Pittsburgh Steelers and won the 2001 XFL championship.
  • E. Thomas
    Thomas is a character appearing in the animated series "Exit 9B" from the show "Regular Show."
  • 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: Thomas
Triple: [Thomas Francis Dorsey Jr., givenName, Thomas]
Generated description
Thomas is a masculine given name of Aramaic origin, widely used in English-speaking countries and historically associated with Christian and Western cultural traditions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Thomas
Target entity description: Thomas is a masculine given name of Aramaic origin, widely used in English-speaking countries and historically associated with Christian and Western cultural traditions.
  • A. Thomas chosen
    Thomas is a common masculine given name of Aramaic origin, widely used in English-speaking and many other cultures.
  • B. Thomas
    Thomas is a common surname of English and Welsh origin, derived from the given name Thomas and borne by numerous notable individuals worldwide.
  • C. Thomas
    Thomas is the given first name of Tom Harmon, the famed American football player and sportscaster.
  • D. Thomas
    Thomas is the given name of Thomas Paine, the influential 18th-century political philosopher and writer known for works like "Common Sense" and "The Rights of Man."
  • E. Thomas
    Thomas is the given name of Thomas Malthus, the influential English economist and demographer known for his theories on population growth and resource limits.
  • 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_69da62636cc08190982cc71733a17b8d completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e66739fde4819083e54f7435405bf0 completed April 20, 2026, 5:49 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0826fe50b481908c6cdefea4e10f8d completed May 16, 2026, 8:12 a.m.
NEDg Description generation batch_6a08295f91f88190868945d0368395bb completed May 16, 2026, 8:22 a.m.
NED2 Entity disambiguation (via description) batch_6a0829c935708190978ed4e447c12585 completed May 16, 2026, 8:24 a.m.
Created at: April 11, 2026, 11:29 p.m.