Triple
T30871575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Irmo, South Carolina |
E786355
|
entity |
| Predicate | majorNearbyEmployer |
P82033
|
FINISHED |
| Object | state government in Columbia |
—
|
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: state government in Columbia | Statement: [Irmo, South Carolina, majorNearbyEmployer, state government in Columbia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorNearbyEmployer Context triple: [Irmo, South Carolina, majorNearbyEmployer, state government in Columbia]
-
A.
hasNearbyEmploymentType
Indicates that one entity has an associated type of employment opportunity located in close physical proximity to another entity.
-
B.
nearbyEconomicActivity
Indicates that there is economic activity occurring in close physical proximity to the referenced entity.
-
C.
hasMajorCompanyNearby
chosen
Indicates that a location or entity is situated close to at least one large or significant company.
-
D.
employerInRegion
Indicates that an employer operates or has its primary business presence within a specified geographic region.
-
E.
worksNear
Indicates that one entity performs its work or duties in close physical proximity to 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_69f224b9df2c819086f55f8bcf7f382e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fe68a4b67881909ca1d9f276f922e0 |
completed | May 8, 2026, 10:50 p.m. |
| PD | Predicate disambiguation | batch_69fe680234c88190b01f953987b74972 |
completed | May 8, 2026, 10:47 p.m. |
Created at: April 29, 2026, 8:48 p.m.