Triple
T22661100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fort Gaines, Georgia |
E559662
|
entity |
| Predicate | regionalDescription |
P35829
|
FINISHED |
| Object | small historic city |
—
|
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: small historic city | Statement: [Fort Gaines, Georgia, regionalDescription, small historic city]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionalDescription Context triple: [Fort Gaines, Georgia, regionalDescription, small historic city]
-
A.
describesRegion
chosen
Indicates that one entity provides a description or characterization of a particular region or area.
-
B.
regionalCharacteristic
Indicates that a particular feature, quality, or attribute is typical of, or distinctive to, a specific geographic region.
-
C.
regionalType
Indicates the classification of a region according to its designated type or category within a broader geographic or administrative system.
-
D.
regionalComponent
Indicates that one entity functions as a sub-region or constituent part within the larger geographic or administrative area represented by the other entity.
-
E.
region1
Indicates that one entity is the first or primary region associated with, containing, or encompassing another entity.
- 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_69e2454a158c819093b8e35f5045efb6 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1765fe7d081908087778c54c1e612 |
completed | April 29, 2026, 3:09 a.m. |
| PD | Predicate disambiguation | batch_69ee6294c4c08190b7e4829f4b9af24b |
completed | April 26, 2026, 7:08 p.m. |
Created at: April 17, 2026, 3:07 p.m.