Triple

T20135292
Position Surface form Disambiguated ID Type / Status
Subject Thomas Rainsborough E491009 entity
Predicate givenName P17 FINISHED
Object Thomas
Thomas is a common masculine given name of Aramaic origin, traditionally interpreted to mean "twin" and widely used in many English-speaking and Christian-influenced cultures.
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 Rainsborough, givenName, Thomas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Thomas
Context triple: [Thomas Rainsborough, 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 Rainsborough, givenName, Thomas]
Generated description
Thomas is a common masculine given name of Aramaic origin, traditionally interpreted to mean "twin" and widely used in many English-speaking and Christian-influenced cultures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Thomas
Target entity description: Thomas is a common masculine given name of Aramaic origin, traditionally interpreted to mean "twin" and widely used in many English-speaking and Christian-influenced cultures.
  • 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 name of Thomas Malthus, the influential English economist and demographer known for his theories on population growth and resource limits.
  • D. Thomas
    Thomas is the given first name of Tom Harmon, the famed American football player and sportscaster.
  • E. 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."
  • 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_69da62651a0c8190a3e05e95e056a66b completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e66766e46c81908721fd47066dc9f8 completed April 20, 2026, 5:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a083c6977e081908d4ef4a0a797eff3 completed May 16, 2026, 9:44 a.m.
NEDg Description generation batch_6a083da579ac8190abd33275c217b1e2 completed May 16, 2026, 9:49 a.m.
NED2 Entity disambiguation (via description) batch_6a083e49d5988190b41e8ce5bcebeca5 completed May 16, 2026, 9:52 a.m.
Created at: April 11, 2026, 11:32 p.m.