Triple
T26092481
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Funza, Cundinamarca |
E658163
|
entity |
| Predicate | secondarySectorOfEconomy |
P62862
|
FINISHED |
| Object | industry and logistics |
—
|
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: industry and logistics | Statement: [Funza, Cundinamarca, secondarySectorOfEconomy, industry and logistics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondarySectorOfEconomy Context triple: [Funza, Cundinamarca, secondarySectorOfEconomy, industry and logistics]
-
A.
economicSectors
Indicates a relationship that associates entities with the economic sectors or industries in which they operate or to which they belong.
-
B.
hasTertiaryEconomicSector
Indicates that an entity participates in or possesses activities belonging to the tertiary (service) sector of the economy, such as services rather than primary or secondary production.
-
C.
hasSecondaryIndustry
chosen
Indicates that an entity is associated with an additional, non-primary industry in which it operates or participates.
-
D.
primarySectorActivity
Indicates the main industry or sector in which an entity primarily conducts its activities or operations.
-
E.
sector
Indicates that an entity operates in, belongs to, or is associated with a particular economic or industrial sector.
- 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_69ee5bbfc4d08190a1b206d0ac3a1e8d |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f6d0d46aec819091edf97324d793ac |
completed | May 3, 2026, 4:36 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe2183481908ae4e85a59c66f69 |
completed | May 3, 2026, 4:32 a.m. |
Created at: April 26, 2026, 7:48 p.m.