Triple
T7222837
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East Alabama region |
E150301
|
entity |
| Predicate | typicalEconomicSectors |
P47145
|
FINISHED |
| Object | manufacturing |
—
|
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: manufacturing | Statement: [East Alabama region, typicalEconomicSectors, manufacturing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalEconomicSectors Context triple: [East Alabama region, typicalEconomicSectors, manufacturing]
-
A.
economicSectorSourceOfWealth
Indicates that a particular economic sector is the primary source from which an entity derives its wealth or income.
-
B.
associatedWithEconomicSector
chosen
Indicates that an entity has a connection or involvement with a particular economic sector, such as operating, participating, or being relevant within that sector.
-
C.
notableSector
Indicates that an entity is particularly prominent, influential, or significant within a specified sector or industry.
-
D.
economicSectorIssue
Indicates that there is a problem, challenge, or concern affecting a particular economic sector.
-
E.
ownerSector
Indicates the sector or industry category to which the owner of an entity belongs.
- 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_69c687effb44819092b95d07d0368c9f |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6e9b54a5c8190a4a289f32853a8fe |
completed | March 27, 2026, 8:33 p.m. |
| PD | Predicate disambiguation | batch_69c6e761b7fc8190857794d78af1b468 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 2:54 p.m.