Triple
T21648826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Groveland, Florida |
E534283
|
entity |
| Predicate | distanceToOrlandoApprox |
P71076
|
FINISHED |
| Object | about 30 miles west |
—
|
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: about 30 miles west | Statement: [Groveland, Florida, distanceToOrlandoApprox, about 30 miles west]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToOrlandoApprox Context triple: [Groveland, Florida, distanceToOrlandoApprox, about 30 miles west]
-
A.
distanceFromOrlando
chosen
Indicates the measured spatial distance between a given place or object and the location of Orlando.
-
B.
distanceToFlorida
Indicates the spatial distance between a given entity’s location and the state of Florida.
-
C.
distanceFromMiami
Indicates the spatial distance between a given entity’s location and the city of Miami.
-
D.
distanceToTallahassee
Indicates the spatial distance between a given entity’s location and the city of Tallahassee.
-
E.
distanceToAtlanta
Indicates the measured or calculated distance between a given location and the city of Atlanta.
- F. None of above.
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_69e0c466aec88190ba39c7543dbc8ba2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef59131c88819082df8e5b87f5954b |
completed | April 27, 2026, 12:39 p.m. |
| PD | Predicate disambiguation | batch_69e696826c3c81909270791e79760937 |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:35 p.m.