Triple
T1762460
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Geoffrey Fisher |
E38686
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Geoffrey |
E28362
|
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: Geoffrey | Statement: [Geoffrey Fisher, givenName, Geoffrey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Geoffrey Context triple: [Geoffrey Fisher, givenName, Geoffrey]
-
A.
Geoffrey
chosen
Geoffrey is a masculine given name of English origin, famously borne by pioneering computer scientist and AI researcher Geoffrey Hinton.
-
B.
Godfrey
Godfrey is the given name of the influential British mathematician G. H. Hardy, renowned for his work in number theory and mathematical analysis.
-
C.
Guillaume
Guillaume is the French form of the given name William, commonly used in French-speaking countries.
-
D.
Rowland
Rowland is the given name of R. H. Macy, the 19th-century American businessman who founded the Macy's department store chain.
-
E.
David of Sassoun
David of Sassoun is a legendary Armenian folk hero and epic warrior celebrated for his superhuman strength and defense of his homeland in the medieval national epic.
- 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_69a8862d562481908d7025a1c1f67c0d |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa6463ac0081909e9ebe6ebf1db857 |
completed | March 6, 2026, 5:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ada98eb0348190a44e05393a2c6eff |
completed | March 8, 2026, 4:53 p.m. |
Created at: March 4, 2026, 7:31 p.m.