Triple

T7573370
Position Surface form Disambiguated ID Type / Status
Subject John Clive Ward E179301 entity
Predicate givenName P17 FINISHED
Object John
John is the given name of John Clive Ward, a notable British-Australian theoretical physicist known for his contributions to quantum electrodynamics and the Ward–Takahashi identity.
E674144 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: John | Statement: [John Clive Ward, givenName, John]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John
Context triple: [John Clive Ward, givenName, John]
  • A. John
    John is the given name of the American composer John Luther Adams, known for his works inspired by nature and environmental themes.
  • B. John
    John is the first name of John Dashwood, a character in Jane Austen's novel "Sense and Sensibility."
  • C. John
    John is the given first name of American character actor and comedian Rags Ragland.
  • D. John
    John is the given name of actor John Cho, a Korean American performer known for roles in the "Harold & Kumar" films and the "Star Trek" reboot series.
  • E. John
    John is the first name of the fictional character John Connor, the prophesied leader of the human resistance in the Terminator franchise.
  • 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: John
Triple: [John Clive Ward, givenName, John]
Generated description
John is the given name of John Clive Ward, a notable British-Australian theoretical physicist known for his contributions to quantum electrodynamics and the Ward–Takahashi identity.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: John
Target entity description: John is the given name of John Clive Ward, a notable British-Australian theoretical physicist known for his contributions to quantum electrodynamics and the Ward–Takahashi identity.
  • A. John
    John is the given name of John Cockcroft, a pioneering British physicist and Nobel laureate known for his work on nuclear physics and particle acceleration.
  • B. John
    John is the given name of the influential American theoretical physicist John Archibald Wheeler, known for his work in quantum mechanics and general relativity.
  • C. John
    John is the given name of John F. Clauser, an American physicist and Nobel laureate known for his pioneering experimental tests of quantum entanglement and Bell's inequalities.
  • D. John
    John is the given name of the British physicist J. J. Thomson, who is best known for discovering the electron and proposing the plum pudding model of the atom.
  • E. John
    John is the given name of John Hasbrouck Van Vleck, an American physicist and Nobel laureate known for his pioneering work in quantum mechanics and magnetism.
  • 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_69c69f316e50819081a271c85c06f918 completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c6f94710a0819094508356b8d610ab completed March 27, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69c861673ae48190b86e8023fd02771c completed March 28, 2026, 11:16 p.m.
NEDg Description generation batch_69c861efe5bc81909ea8eb9ddcd7cd82 completed March 28, 2026, 11:19 p.m.
NED2 Entity disambiguation (via description) batch_69c86259a5888190a6fb6a8564188d54 completed March 28, 2026, 11:20 p.m.
Created at: March 27, 2026, 3:51 p.m.