Triple

T10072842
Position Surface form Disambiguated ID Type / Status
Subject Michael Tilson Thomas E213671 entity
Predicate familyName P18 FINISHED
Object Thomas
Thomas is a common English-language surname of biblical origin, borne by numerous notable figures across history and culture.
E251923 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: [Michael Tilson Thomas, familyName, Thomas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Thomas
Context triple: [Michael Tilson Thomas, familyName, Thomas]
  • A. John
    John is the husband of Martha Rainsborough.
  • B. John
    John is the given name of Colonel John Quincy, an American military officer and politician after whom John Quincy Adams was named.
  • C. John
    John is the given name of John Henry Patterson, an American industrialist and founder of the National Cash Register Company.
  • D. John
    John is the first name of J. Michael Luttig, a prominent American conservative jurist and former federal appellate judge.
  • E. 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.
  • 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: [Michael Tilson Thomas, familyName, Thomas]
Generated description
Thomas is a common English-language surname of biblical origin, borne by numerous notable figures across history and culture.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Thomas
Target entity description: Thomas is a common English-language surname of biblical origin, borne by numerous notable figures across history and culture.
  • A. Thomas chosen
    Thomas is a common surname of English and Welsh origin, derived from the given name Thomas and borne by numerous notable individuals worldwide.
  • B. Thomas
    Thomas is a common masculine given name of Aramaic origin, widely used in English-speaking and many other cultures.
  • C. 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."
  • D. 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.
  • E. Thomas
    Thomas is the given name of Thomas Cranmer, the 16th-century Archbishop of Canterbury and a leading figure in the English Reformation.
  • 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_69ca839add308190b57d53b4ec21f2d0 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdd013c9d0819091ebe6fc399832de completed April 2, 2026, 2:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69d29a4064a48190b4fdb6bf3ea5af05 completed April 5, 2026, 5:22 p.m.
NEDg Description generation batch_69d29b28f48081909f7e0487800ebe52 completed April 5, 2026, 5:26 p.m.
NED2 Entity disambiguation (via description) batch_69d29be3713c819089843c4ec2be93f1 completed April 5, 2026, 5:29 p.m.
Created at: March 30, 2026, 8:59 p.m.