Triple
T12033542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marion County, Florida |
E286473
|
entity |
| Predicate | largestCity |
P235
|
FINISHED |
| Object | Ocala, Florida |
E611483
|
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: Ocala, Florida | Statement: [Marion County, Florida, largestCity, Ocala, Florida]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ocala, Florida Context triple: [Marion County, Florida, largestCity, Ocala, Florida]
-
A.
Ocala
Ocala is a city in north-central Florida known for its thoroughbred horse farms and historic downtown.
-
B.
Ocala, Florida, United States
chosen
Ocala is a mid-sized city in north-central Florida known for its thoroughbred horse farms and historic downtown.
-
C.
Seminole, Florida
Seminole, Florida is a small suburban city in the Tampa Bay area known for its residential communities, parks, and proximity to Gulf Coast beaches.
-
D.
Eustis, Florida
Eustis, Florida is a small central Florida city known for its historic downtown, access to nearby lakes, and role as part of the Orlando–Kissimmee–Sanford metropolitan area.
-
E.
Ochopee, Florida
Ochopee, Florida is a tiny unincorporated community in the Florida Everglades best known for having one of the smallest post offices in the United States.
- 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_69d6ab4669e48190b59246358b0383ab |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9040724ec8190808f334013ddc6d6 |
completed | April 10, 2026, 2:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60a613054819082f7900a6ba8fbf8 |
completed | May 2, 2026, 2:29 p.m. |
Created at: April 8, 2026, 9:47 p.m.