Triple
T1196164
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mayabeque Province |
E25671
|
entity |
| Predicate | hasIndustrialActivity |
P1099
|
FINISHED |
| Object | food processing |
—
|
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: food processing | Statement: [Mayabeque Province, hasIndustrialActivity, food processing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIndustrialActivity Context triple: [Mayabeque Province, hasIndustrialActivity, food processing]
-
A.
hasIndustrialSector
Indicates that an entity is associated with, operates in, or belongs to a particular industrial sector or branch of economic activity.
-
B.
hasIndustrialPark
Indicates that a location or entity possesses or contains an industrial park within its area or jurisdiction.
-
C.
hasEconomicActivity
chosen
Indicates that an entity engages in, supports, or is associated with a specific type of economic activity or business operation.
-
D.
isIndustrialRegion
Indicates that a given area functions primarily as a center of industrial activity, characterized by significant manufacturing, production, or related industrial operations.
-
E.
isIndustrialCenter
Indicates that a place functions as a major hub of industrial activity, production, or manufacturing within a region.
- 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_69a49429f5ec8190a6a205eb0ae81e5e |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd7a756c819085d695acfffeaceb |
completed | March 1, 2026, 10:28 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5d40a08190b7682d8ef8075421 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:46 p.m.