Triple

T16381544
Position Surface form Disambiguated ID Type / Status
Subject Robin Warren E397818 entity
Predicate givenName P17 FINISHED
Object John
John is the given first name of Australian pathologist Robin Warren, who won the Nobel Prize for discovering the role of Helicobacter pylori in gastritis and peptic ulcers.
E1210120 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: [Robin Warren, givenName, John]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John
Context triple: [Robin Warren, 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 first name of Jack Phillips, the British wireless operator on the RMS Titanic who died during its sinking in 1912.
  • E. John
    John is the given name of John Maitland, 1st Duke of Lauderdale, a prominent 17th-century Scottish nobleman and statesman.
  • 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: [Robin Warren, givenName, John]
Generated description
John is the given first name of Australian pathologist Robin Warren, who won the Nobel Prize for discovering the role of Helicobacter pylori in gastritis and peptic ulcers.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: John
Target entity description: John is the given first name of Australian pathologist Robin Warren, who won the Nobel Prize for discovering the role of Helicobacter pylori in gastritis and peptic ulcers.
  • A. John
    John is the given name of John James Rickard Macleod, the Scottish physiologist and co-recipient of the 1923 Nobel Prize in Physiology or Medicine for the discovery of insulin.
  • B. John
    John is the given name of John Boyd Orr, a Scottish nutritionist and politician who won the Nobel Peace Prize for his work on global food policy and security.
  • C. John
    John is the given first name of J. Michael Bishop, the American immunologist and Nobel Prize–winning scientist known for his work on oncogenes.
  • D. John
    John is the given name of John B. Gurdon, a Nobel Prize–winning British developmental biologist known for his pioneering work in nuclear reprogramming and cloning.
  • E. John
    John is the given name of John Polanyi, a Nobel Prize–winning chemist known for his work on chemical kinetics and reaction dynamics.
  • 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_69d87f2880b48190ae1a9673a3bbef80 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e319dd0e0c8190812bde6a2f7d9644 completed April 18, 2026, 5:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0035587c3481908448f75e5a56d2cb completed May 10, 2026, 7:35 a.m.
NEDg Description generation batch_6a00364b277c8190b1423f8bbe42be0d completed May 10, 2026, 7:39 a.m.
NED2 Entity disambiguation (via description) batch_6a0036d16a648190b5aab78fb21dad72 completed May 10, 2026, 7:42 a.m.
Created at: April 10, 2026, 5:08 a.m.