Triple

T10175425
Position Surface form Disambiguated ID Type / Status
Subject Thomas Joseph Power E235839 entity
Predicate givenName P17 FINISHED
Object Thomas
Thomas is a common masculine given name of Aramaic origin meaning "twin," 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 Joseph Power, givenName, Thomas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Thomas
Context triple: [Thomas Joseph Power, givenName, Thomas]
  • A. John
    John Seigenthaler was an American journalist, editor, and civil rights advocate best known for his long tenure at The Tennessean and his work promoting First Amendment rights.
  • B. John
    John is the given name of John Vlissides, a software engineer best known as one of the “Gang of Four” authors of the influential book *Design Patterns: Elements of Reusable Object-Oriented Software*.
  • C. John
    John is the given name of Sir John Woodville, a 15th-century English nobleman associated with the influential Woodville family during the Wars of the Roses.
  • D. John
    John is the given name of Lord Eldon, a prominent British lawyer and politician who served as Lord Chancellor in the early 19th century.
  • E. John
    John Bacon was a 19th-century American politician who served in the Wisconsin State Assembly.
  • 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 Joseph Power, givenName, Thomas]
Generated description
Thomas is a common masculine given name of Aramaic origin meaning "twin," 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 meaning "twin," 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 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 first name of English actor Tom Sturridge, known for his work in film, television, and theatre.
  • 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_69ca84d1d5f88190ab878a1021ecff68 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdecd26a8c8190a391b9d5e47ebb72 completed April 2, 2026, 4:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69d354e57ea88190922e7eee07fd86f2 completed April 6, 2026, 6:38 a.m.
NEDg Description generation batch_69d358df8b8c8190b79b9b31f1f89311 completed April 6, 2026, 6:55 a.m.
NED2 Entity disambiguation (via description) batch_69d359547f6881908fa8830dc65beabc completed April 6, 2026, 6:57 a.m.
Created at: March 30, 2026, 9:11 p.m.