Triple
T14692943
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elton Mayo |
E345080
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
George
George is the given first name of Elton Mayo, the influential Australian-born psychologist and organizational theorist known for the Hawthorne Studies in industrial sociology.
|
E1114966
|
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: George | Statement: [Elton Mayo, givenName, George]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: George Context triple: [Elton Mayo, givenName, George]
-
A.
George
George is the given first name of the fictional character Gob Bluth from the television series "Arrested Development."
-
B.
George
George is the middle name of William George Barker, a renowned Canadian World War I flying ace and Victoria Cross recipient.
-
C.
George
George is the given name of George Stanley, 9th Baron Strange, an English nobleman and politician of the late 15th century.
-
D.
George
George is the given name of George Carnegie, 6th Earl of Northesk, a Scottish nobleman and naval officer in the Royal Navy.
-
E.
George
George is the given name of Lord George Murray, a prominent Scottish Jacobite general during the 18th-century uprisings.
- 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: George Triple: [Elton Mayo, givenName, George]
Generated description
George is the given first name of Elton Mayo, the influential Australian-born psychologist and organizational theorist known for the Hawthorne Studies in industrial sociology.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: George Target entity description: George is the given first name of Elton Mayo, the influential Australian-born psychologist and organizational theorist known for the Hawthorne Studies in industrial sociology.
-
A.
George
George is the given name of George Ellery Hale, the influential American solar astronomer and founder of several major observatories.
-
B.
George
George is the given first name of G. Ledyard Stebbins, a prominent American botanist and evolutionary biologist.
-
C.
George
George is the given name of George de Hevesy, the Hungarian radiochemist and Nobel laureate known for pioneering the use of radioactive tracers in studying chemical processes.
-
D.
George
George is the given name of George Bellas Greenough, a pioneering 19th-century English geologist and founding figure of the Geological Society of London.
-
E.
George
George is the given name of George C. Pimentel, a prominent American chemist known for his work in chemical lasers and molecular spectroscopy.
- 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_69d822e34b348190ada4d1cdb6c7c226 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb586e7108190be644db9cf9a4d99 |
completed | April 14, 2026, 9:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdf08274ac8190b5ba0752d36a690b |
completed | May 8, 2026, 2:17 p.m. |
| NEDg | Description generation | batch_69fdf21ff584819098d5bc66fd667edf |
completed | May 8, 2026, 2:24 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fdf2980d188190a81474df8097aab7 |
completed | May 8, 2026, 2:26 p.m. |
Created at: April 10, 2026, 1:28 a.m.