Triple
T13254057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Finley |
E315610
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Finley |
E451750
|
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: Finley | Statement: [Robert Finley, familyName, Finley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Finley Context triple: [Robert Finley, familyName, Finley]
-
A.
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.
-
B.
Finley
chosen
Finley is a surname of English and Scottish origin borne by various notable individuals across sports, politics, and the arts.
-
C.
Finley Hobbins
Finley Hobbins is a young American actor best known for his role in Disney’s live-action adaptation of "Dumbo" (2019).
-
D.
Finley Nantz
Finley Nantz is the daughter of renowned American sportscaster Jim Nantz.
-
E.
Keefer
Keefer was a distinguished racing greyhound renowned for its achievements on the track, earning induction into the Greyhound Hall of Fame.
- 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_69d806b1072881909e46bd212259c5f0 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98f7517048190b4eac4e44e81ff66 |
completed | April 11, 2026, 12:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f70a3d6b808190b4ae5225961de03f |
completed | May 3, 2026, 8:41 a.m. |
Created at: April 9, 2026, 9:24 p.m.