Triple

T17119876
Position Surface form Disambiguated ID Type / Status
Subject Tom Tancredo E415436 entity
Predicate givenName P17 FINISHED
Object Thomas
Thomas is the given name of American politician Tom Tancredo, a former U.S. Representative from Colorado known for his hardline stance on immigration.
 E1253171 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: [Tom Tancredo, givenName, Thomas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Thomas
Context triple: [Tom Tancredo, givenName, Thomas]
  • A. Thomas
    Thomas is the birth name of American actor, comedian, and musician Jack Black, known for films like "School of Rock" and as the lead vocalist of Tenacious D.
  • B. Thomas
    Thomas is the given name of Old Tom Morris, the 19th-century Scottish golfer regarded as a pioneer and four-time Open Championship winner.
  • C. Thomas
    Thomas is the first name of American country music singer and songwriter Luke Bryan.
  • D. Thomas
    Thomas is the given name of Sir Stamford Raffles, the British statesman best known as the founder of modern Singapore.
  • 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. 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: [Tom Tancredo, givenName, Thomas]
Generated description
Thomas is the given name of American politician Tom Tancredo, a former U.S. Representative from Colorado known for his hardline stance on immigration.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Thomas
Target entity description: Thomas is the given name of American politician Tom Tancredo, a former U.S. Representative from Colorado known for his hardline stance on immigration.
  • A. Thomas
    Thomas is the given name of American politician Tom DeLay, a former House Majority Leader known for his influential role in U.S. Republican politics in the 1990s and early 2000s.
  • B. Thomas
    Thomas is the given first name of Tip O'Neill, the long-serving Speaker of the United States House of Representatives.
  • C. Thomas
    Thomas is the first name of Slade Gorton, an American politician who served as a U.S. Senator from Washington.
  • D. Thomas
    Thomas is the first name of Tom Ridge, the former governor of Pennsylvania and the first United States Secretary of Homeland Security.
  • E. Thomas
    Thomas is the full given name of Tom Osborne, the renowned former University of Nebraska football coach and U.S. congressman.
  • 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_69d886d090cc8190a39cb94992586905 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3e8092b548190b45c1695be47edc2 completed April 18, 2026, 8:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0141422d6c819086dc98988c0851d9 completed May 11, 2026, 2:38 a.m.
NEDg Description generation batch_6a01437dd094819093603356fa2c2582 completed May 11, 2026, 2:48 a.m.
NED2 Entity disambiguation (via description) batch_6a014416c6a08190aeca937990d2b5a2 completed May 11, 2026, 2:51 a.m.
Created at: April 10, 2026, 5:36 a.m.