Triple
T19554147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TigerTown complex |
E489263
|
entity |
| Predicate | city |
P40
|
FINISHED |
| Object | Lakeland |
—
|
NE NERFINISHED |
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: Lakeland | Statement: [TigerTown complex, city, Lakeland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lakeland Context triple: [TigerTown complex, city, Lakeland]
-
A.
Lakeland
Lakeland is a residential neighborhood located within the city of College Park in Prince George's County, Maryland.
-
B.
Lakeland, Florida
chosen
Lakeland, Florida is a mid-sized city in central Florida known for its numerous lakes, historic downtown, and long-standing ties to Major League Baseball.
-
C.
Ocala
Ocala is a city in north-central Florida known for its thoroughbred horse farms and historic downtown.
-
D.
Polk City
Polk City is a small community in central Iowa known for its proximity to Saylorville Lake and Big Creek State Park.
-
E.
Eustis
Eustis is a surname of English origin borne by various notable individuals, including military figures and public officials in American history.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8dc5d8c8190a6d7bd8864f43ca0 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63d3254548190828a5f7e9a851ef8 |
completed | April 20, 2026, 2:50 p.m. |
Created at: April 10, 2026, 1:41 p.m.