Triple
T647252
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Florida Keys |
E11266
|
entity |
| Predicate | isSouthernmostPartOf |
P17679
|
FINISHED |
| Object | contiguous United States |
—
|
LITERAL 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: contiguous United States | Statement: [Florida Keys, isSouthernmostPartOf, contiguous United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isSouthernmostPartOf Context triple: [Florida Keys, isSouthernmostPartOf, contiguous United States]
-
A.
southernmostDistrictOf
Indicates that one district is the geographically furthest south within the boundaries of a specified larger region or entity.
-
B.
southernmostCityOf
Indicates that one city is the geographically furthest south among all cities within a specified region or set.
-
C.
locatedSouthOf
Indicates that one entity is positioned geographically to the south of another entity.
-
D.
locatedSouthWestOf
Indicates that one entity is positioned to the southwest of another entity, combining both a southern and western relative location.
-
E.
liesSoutheastOf
Indicates that one entity is located to the southeast of another, combining both a southern and eastern directional relationship.
- F. None of above. chosen
Provenance (4 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_69a493266a2881909daf4c40f719dee8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49f1cb24481909d3b41a56b29dee9 |
completed | March 1, 2026, 8:18 p.m. |
| PD | Predicate disambiguation | batch_69a49d0c0dcc8190849211d45489a5a7 |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49df0de3c81909721eb391ec94031 |
completed | March 1, 2026, 8:13 p.m. |
Created at: March 1, 2026, 7:36 p.m.