Triple

T23931417
Position Surface form Disambiguated ID Type / Status
Subject Matthew Flinders Medal E602507 entity
Predicate notableRecipient P108 FINISHED
Object Graeme Jameson
Graeme Jameson is an Australian chemical engineer renowned for inventing the Jameson Cell flotation technology, which revolutionized mineral processing and earned him major scientific and engineering honors.
E1656054 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: Graeme Jameson | Statement: [Matthew Flinders Medal, notableRecipient, Graeme Jameson]
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: Graeme Jameson
Triple: [Matthew Flinders Medal, notableRecipient, Graeme Jameson]
Generated description
Graeme Jameson is an Australian chemical engineer renowned for inventing the Jameson Cell flotation technology, which revolutionized mineral processing and earned him major scientific and engineering honors.

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_69e2953b928c819095395fa87baca583 completed April 17, 2026, 8:16 p.m.
NER Named-entity recognition batch_69f1cf9c223881908e5fa4b5564848e6 completed April 29, 2026, 9:30 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1032d2a29c81909d1ed03645c0dab5 completed May 22, 2026, 10:41 a.m.
NEDg Description generation batch_6a10341e764c819083c10e4d151da1c6 completed May 22, 2026, 10:46 a.m.
NED2 Entity disambiguation (via description) batch_6a1034c45fb88190865f904fd8e766b3 completed May 22, 2026, 10:49 a.m.
Created at: April 17, 2026, 8:58 p.m.