Triple

T14774905
Position Surface form Disambiguated ID Type / Status
Subject John B. Fenn E347233 entity
Predicate givenName P17 FINISHED
Object 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.
E1121369 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 B. Fenn, givenName, John]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John
Context triple: [John B. Fenn, givenName, John]
  • A. John
    John is the given first name of Johnny Kilbane, an American featherweight boxing champion from the early 20th century.
  • B. John
    John is the middle name of Samuel John Mills, an American Congregationalist minister known for his role in early 19th-century missionary movements.
  • C. John
    John is the given name of John C. Sheehan, an American organic chemist renowned for achieving the first complete laboratory synthesis of penicillin.
  • D. John
    John was a Portuguese royal who held the title of Prince of Brazil and later became King John VI of Portugal.
  • E. John
    John is the given name of John Boyle O'Reilly, a 19th-century Irish-born poet, journalist, and civil rights activist who became influential in the United States.
  • 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 B. Fenn, givenName, John]
Generated description
John is the given name of John B. Fenn, the American chemist and Nobel laureate known for his work in electrospray ionization mass spectrometry.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: John
Target entity description: John is the given name of John B. Fenn, the American chemist and Nobel laureate known for his work in electrospray ionization mass spectrometry.
  • A. John
    John is the given name of John Polanyi, a Nobel Prize–winning chemist known for his work on chemical kinetics and reaction dynamics.
  • 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 Cockcroft, a pioneering British physicist and Nobel laureate known for his work on nuclear physics and particle acceleration.
  • D. John
    John is the given name of Sir John Lennard-Jones, a pioneering British theoretical chemist known for his work on intermolecular forces and the Lennard-Jones potential.
  • E. John
    John is the given name of John C. Sheehan, an American organic chemist renowned for achieving the first complete laboratory synthesis of penicillin.
  • 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_69d822e9b9e08190bedcc31a163fda82 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec815dd5081909e927911c06b2d66 completed April 14, 2026, 11:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe24ac17888190bda346df75d37620 completed May 8, 2026, 6 p.m.
NEDg Description generation batch_69fe357d7ae0819085ad5f31ef5722a0 completed May 8, 2026, 7:11 p.m.
NED2 Entity disambiguation (via description) batch_69fe361cd7188190adb9c57314de9276 completed May 8, 2026, 7:14 p.m.
Created at: April 10, 2026, 1:31 a.m.