Triple
T38079894
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UGA–GT rivalry |
E950821
|
entity |
| Predicate | cityAssociationGT |
P24465
|
FINISHED |
| Object | Atlanta, Georgia |
—
|
NE NERFINISHED |
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: Atlanta, Georgia | Statement: [UGA–GT rivalry, cityAssociationGT, Atlanta, Georgia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityAssociationGT Context triple: [UGA–GT rivalry, cityAssociationGT, Atlanta, Georgia]
-
A.
cityAssociatedWith
chosen
Indicates that there is a notable connection or relationship between a city and another entity, such as relevance, involvement, or contextual association.
-
B.
cityCluster
Indicates a grouping relationship where multiple cities are associated together as part of the same cluster or urban agglomeration.
-
C.
cityGroupType
Indicates the classification or category type assigned to a group of cities within a larger organizational or geographic structure.
-
D.
associatedWithCityGroup
Indicates a relationship where an entity is linked or connected to a specific group or collection of cities.
-
E.
connectsCity
Indicates a relationship where one entity serves as a link or route that joins or provides direct access between two cities.
- 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_69f76f03a3608190a73fd6df87c792a8 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fccbd826708190b5fab12c4236299a |
completed | May 7, 2026, 5:28 p.m. |
| PD | Predicate disambiguation | batch_69fcc58838e08190b8fa54aa5c165f2d |
completed | May 7, 2026, 5:02 p.m. |
Created at: May 3, 2026, 4:21 p.m.