Triple

T23962079
Position Surface form Disambiguated ID Type / Status
Subject Jens Christian Skou E603953 entity
Predicate NobelPrize.sharedWith P1859 FINISHED
Object John E. Walker
John E. Walker is a British biochemist and Nobel Prize laureate renowned for elucidating the enzymatic mechanism of ATP synthase, a key enzyme in cellular energy production.
E1623034 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: John E. Walker | Statement: [Jens Christian Skou, NobelPrize.sharedWith, John E. Walker]
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 E. Walker
Triple: [Jens Christian Skou, NobelPrize.sharedWith, John E. Walker]
Generated description
John E. Walker is a British biochemist and Nobel Prize laureate renowned for elucidating the enzymatic mechanism of ATP synthase, a key enzyme in cellular energy production.

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_69e2954222288190a7323554d0cca8d7 completed April 17, 2026, 8:17 p.m.
NER Named-entity recognition batch_69f1d0dac8e081908286e8d8d30784ee completed April 29, 2026, 9:35 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fbcf0f64c8190b26b0815969596be completed May 22, 2026, 2:18 a.m.
NEDg Description generation batch_6a0fbd9cd4b08190a8191001ca5d2b6f completed May 22, 2026, 2:21 a.m.
NED2 Entity disambiguation (via description) batch_6a0fbe0f87fc8190afddc29089373c2f completed May 22, 2026, 2:23 a.m.
Created at: April 17, 2026, 9:23 p.m.