Triple

T23091355
Position Surface form Disambiguated ID Type / Status
Subject John W. Cahn E575757 entity
Predicate givenName P17 FINISHED
Object John
John is the given name of John W. Cahn, an influential American materials scientist and physicist known for his pioneering work in phase transformations and materials thermodynamics.
E575757 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 W. Cahn, givenName, John]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John
Context triple: [John W. Cahn, givenName, John]
  • A. John
    John is the given name of John J. Pershing, the famed American general who led the American Expeditionary Forces in World War I.
  • B. John
    John is the given name of John A. Roebling II, an American civil engineer and philanthropist from the prominent Roebling family associated with major bridge construction.
  • C. John
    John is the given first name of Johnny Kilbane, an American featherweight boxing champion from the early 20th century.
  • D. John
    John is the given name of John Albert William Spencer-Churchill, a British aristocrat and 10th Duke of Marlborough.
  • E. John
    John is the given name of John Williams Walker, an early 19th-century American politician and U.S. Senator from Alabama.
  • 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 W. Cahn, givenName, John]
Generated description
John is the given name of John W. Cahn, an influential American materials scientist and physicist known for his pioneering work in phase transformations and materials thermodynamics.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: John
Target entity description: John is the given name of John W. Cahn, an influential American materials scientist and physicist known for his pioneering work in phase transformations and materials thermodynamics.
  • A. John chosen
    John is the given name of John W. Cahn, a prominent American materials scientist known for his influential work in the theory of phase transformations and materials microstructure.
  • B. John
    John is the given name of the American chemist John F. Hartwig, renowned for his pioneering work in organometallic chemistry and catalysis.
  • C. 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.
  • D. John
    John is the given name of John Gamble Kirkwood, an influential American theoretical chemist and physicist known for his work in statistical mechanics and molecular theory.
  • E. John
    John is the given name of John B. Fenn, the American chemist and Nobel laureate known for his work in electrospray ionization mass spectrometry.
  • 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_69e245bf3e3c819086d3448720efc01b completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f18daa68d48190842e9cb6de31ea79 completed April 29, 2026, 4:48 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c159ffb7481909b2987e8aea047ca completed May 19, 2026, 7:47 a.m.
NEDg Description generation batch_6a0c17214dc48190be02f8d83c29b90a completed May 19, 2026, 7:54 a.m.
NED2 Entity disambiguation (via description) batch_6a0c17da6a108190b37d1e69e6f24e00 completed May 19, 2026, 7:57 a.m.
Created at: April 17, 2026, 3:57 p.m.