Triple
T6351
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warm Springs, Georgia |
E127
|
entity |
| Predicate | isTouristDestinationFor |
P530
|
FINISHED |
| Object | historic tourism |
—
|
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: historic tourism | Statement: [Warm Springs, Georgia, isTouristDestinationFor, historic tourism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isTouristDestinationFor Context triple: [Warm Springs, Georgia, isTouristDestinationFor, historic tourism]
-
A.
isTouristDestination
chosen
Indicates that a place is recognized as a location people commonly visit for leisure, sightseeing, or travel.
-
B.
isMajorCenterOf
Indicates that a place serves as a primary hub or focal point for a particular activity, function, or domain.
-
C.
hasMajorCity
Indicates that a location possesses at least one city of significant size, importance, or influence within its region or country.
-
D.
locatedAcrossRiverFrom
Indicates that one entity is situated on the opposite side of a river relative to another entity.
-
E.
isPortCityOn
Indicates that a city functions as a port located on the specified body of water.
- 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_69a23bb612708190b09f25385e4b63d1 |
completed | Feb. 28, 2026, 12:49 a.m. |
| NER | Named-entity recognition | batch_69a2421836f08190b54fc40edeb1a96b |
completed | Feb. 28, 2026, 1:17 a.m. |
| PD | Predicate disambiguation | batch_69a23fe064c881909496fd0e6b0e18d7 |
completed | Feb. 28, 2026, 1:07 a.m. |
Created at: Feb. 28, 2026, 12:54 a.m.