Triple
T35279292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Region |
E1018890
|
entity |
| Predicate | relativeLocationWithinUS |
P56631
|
FINISHED |
| Object | southeastern United States |
—
|
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: southeastern United States | Statement: [South Region, relativeLocationWithinUS, southeastern United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relativeLocationWithinUS Context triple: [South Region, relativeLocationWithinUS, southeastern United States]
-
A.
regionalLocationWithinState
Indicates that one region is geographically located within the boundaries of a specific state.
-
B.
nearbyState
Indicates that one state is geographically adjacent to or in close proximity to another state.
-
C.
hasRelativePositionInCity
Indicates that one entity occupies a specific spatial or positional relationship within the boundaries or layout of a particular city.
-
D.
hasNearbyUSCity
Indicates that one location has at least one city in the United States situated within a specified nearby distance.
-
E.
locatedInUSRegion
chosen
Indicates that one entity is geographically situated within a specified region of the United States.
- 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_69f76de5c4788190896ad598ae7d6bc6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0324d08190ac5b610cc0f6a38c |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:02 p.m.