Triple
T16287208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Higgston, Georgia |
E395418
|
entity |
| Predicate | hasGeneralRegionType |
P122538
|
FINISHED |
| Object | rural area |
—
|
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: rural area | Statement: [Higgston, Georgia, hasGeneralRegionType, rural area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGeneralRegionType Context triple: [Higgston, Georgia, hasGeneralRegionType, rural area]
-
A.
containsRegionType
Indicates that one region includes or encompasses another region of a specified type within its spatial or logical boundaries.
-
B.
hasGlobalRegion
Indicates that an entity is associated with or belongs to a specific global geographic region.
-
C.
hasBaseRegion
Indicates that one entity is situated upon, supported by, or primarily associated with a specific underlying region or area.
-
D.
hasRegion
Indicates that an entity includes, contains, or is associated with a specific geographic or administrative region as part of its scope or structure.
-
E.
hasTypicalUsageRegion
Indicates that something is most commonly or characteristically used within a particular geographic region.
- 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_69d87f22c7248190a54c949738441e2e |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e24915a5948190a11b8e83b7974dda |
completed | April 17, 2026, 2:52 p.m. |
| PD | Predicate disambiguation | batch_69e219f68d308190b71c1601303f0628 |
completed | April 17, 2026, 11:31 a.m. |
| PDg | Predicate description generation | batch_69e21e56e0348190a3d9475360231a70 |
completed | April 17, 2026, 11:49 a.m. |
Created at: April 10, 2026, 5:05 a.m.