Triple
T10071983
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rio Largo |
E213650
|
entity |
| Predicate | economicImportanceInState |
P14281
|
FINISHED |
| Object | important sugarcane-producing municipality of Alagoas |
—
|
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: important sugarcane-producing municipality of Alagoas | Statement: [Rio Largo, economicImportanceInState, important sugarcane-producing municipality of Alagoas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: economicImportanceInState Context triple: [Rio Largo, economicImportanceInState, important sugarcane-producing municipality of Alagoas]
-
A.
hasEconomicImportanceFor
chosen
Indicates that one entity holds economic value, benefit, or significance for another entity.
-
B.
economicImpactRegion
Indicates the region or geographic area that experiences or is affected by a particular economic impact.
-
C.
economicSectorSourceOfWealth
Indicates that a particular economic sector is the primary source from which an entity derives its wealth or income.
-
D.
regionalEconomyType
Indicates the type or classification of an economy associated with a specific region.
-
E.
hasCommercialImportance
Indicates that something possesses economic or business value significant enough to impact trade, revenue, or market activity.
- 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_69ca839add308190b57d53b4ec21f2d0 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd01279388190b94c8def00425c78 |
completed | April 2, 2026, 2:10 a.m. |
| PD | Predicate disambiguation | batch_69cd4b97870481908f7a89df10d58a9e |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 8:59 p.m.