Triple

T1727638
Position Surface form Disambiguated ID Type / Status
Subject Corn Laws debate E37533 entity
Predicate significantPerson P643 FINISHED
Object Thomas Tooke E39969 NE FINISHED

How this triple was built (2 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 Tooke | Statement: [Corn Laws debate, significantPerson, Thomas Tooke]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Thomas Tooke
Context triple: [Corn Laws debate, significantPerson, Thomas Tooke]
  • A. Thomas Tooke chosen
    Thomas Tooke was a 19th-century British economist and statistician best known for his pioneering work on price history and monetary theory, particularly through his multi-volume "History of Prices."
  • B. Thomas Tickell
    Thomas Tickell was an early 18th-century English poet and translator associated with Joseph Addison and the Whig literary circle.
  • C. Robert Torrens
    Robert Torrens was a 19th-century Irish-born British economist, politician, and influential early theorist of international trade and comparative advantage.
  • D. Gilbert Wakefield
    Gilbert Wakefield was an 18th-century English scholar, classical critic, and controversial theologian known for his radical political views and biblical scholarship.
  • E. George Wells
    George Wells was an American screenwriter known for his work on classic Hollywood films, including several MGM musicals and comedies.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69a8861acab88190bb43cde203429399 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa637c26988190ad5c400856684825 completed March 6, 2026, 5:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada0d76ea481908227f9cad3ff4523 completed March 8, 2026, 4:16 p.m.
Created at: March 4, 2026, 7:30 p.m.