Triple
T7939421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Google Borg |
E184354
|
entity |
| Predicate | authorsInclude |
P63068
|
FINISHED |
| Object | John Wilkes |
E107833
|
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 Wilkes | Statement: [Google Borg, authorsInclude, John Wilkes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Wilkes Context triple: [Google Borg, authorsInclude, John Wilkes]
-
A.
John Wilkes
chosen
John Wilkes was an 18th-century English radical politician, journalist, and champion of civil liberties who became a symbol of the fight for parliamentary reform.
-
B.
Thomas Tickell
Thomas Tickell was an early 18th-century English poet and translator associated with Joseph Addison and the Whig literary circle.
-
C.
James Widdoes
James Widdoes is an American actor, director, and television producer best known for directing and producing numerous sitcoms, including extensive work on series like Two and a Half Men and Mom.
-
D.
Thomas Burke
Thomas Burke was an American politician who served as the third Governor of North Carolina during the early years of the United States.
-
E.
Thomas Burke
Thomas Burke was a British author best known for his early 20th-century stories set in London’s East End, including the tale that inspired the film "Broken Blossoms."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca8290c21c8190906a5ca6fe2b03c4 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3b0983388190a77e8d5d899c5130 |
completed | March 31, 2026, 3:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5c0e868481908748d340244ea8ea |
completed | March 31, 2026, 5:30 a.m. |
Created at: March 30, 2026, 5:08 p.m.