Triple
T6342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warm Springs, Georgia |
E127
|
entity |
| Predicate | hasNaturalFeature |
P1094
|
FINISHED |
| Object | warm mineral springs |
—
|
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: warm mineral springs | Statement: [Warm Springs, Georgia, hasNaturalFeature, warm mineral springs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNaturalFeature Context triple: [Warm Springs, Georgia, hasNaturalFeature, warm mineral springs]
-
A.
hasRiver
Indicates that a location or area contains, is traversed by, or is directly associated with a river.
-
B.
hasCoastlineOn
Indicates that one entity’s coastline borders or is directly adjacent to a specified body of water.
-
C.
GNISFeatureID
Indicates that an entity is associated with a specific identifier assigned by the U.S. Geological Survey’s Geographic Names Information System (GNIS) to uniquely reference a geographic feature.
-
D.
hasClimate
Indicates that an entity possesses or is characterized by a particular type of climate or climatic conditions.
-
E.
basinCountry
Indicates the country or countries within whose territory a river basin or drainage area is primarily located or through which it significantly extends.
- 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_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. |
| PDg | Predicate description generation | batch_69a242174cd4819095f78b221e1b41f1 |
completed | Feb. 28, 2026, 1:17 a.m. |
Created at: Feb. 28, 2026, 12:54 a.m.