Triple
T7899029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hal Finney |
E183402
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Finney |
E335360
|
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: Finney | Statement: [Hal Finney, familyName, Finney]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Finney Context triple: [Hal Finney, familyName, Finney]
-
A.
Finney
chosen
Finney is a surname most famously associated with English actor Albert Finney, known for his acclaimed work in film, television, and theatre.
-
B.
Feeney
Feeney is an Irish-origin surname borne by various notable figures in fields such as film, sports, and public life.
-
C.
Fay
Fay is a given name most famously associated with Canadian-American actress Fay Wray, the iconic star of the 1933 film "King Kong."
-
D.
Finley
Finley is a surname of English and Scottish origin borne by various notable individuals across sports, politics, and the arts.
-
E.
Finley
Finley is a small rural town in the Riverina region of New South Wales, Australia, known for its agricultural community and irrigation-based farming.
- 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_69ca828d13088190b222be7aa9f9315c |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a2ae5048190a6824d34b582c366 |
completed | March 31, 2026, 3:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5bb719a08190a0545a361f559bf7 |
completed | March 31, 2026, 5:29 a.m. |
Created at: March 30, 2026, 5:01 p.m.