Triple
T1728859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madrid, Cundinamarca |
E37562
|
entity |
| Predicate | flowerIndustryRole |
P31241
|
FINISHED |
| Object | export-oriented cut flower production center |
—
|
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: export-oriented cut flower production center | Statement: [Madrid, Cundinamarca, flowerIndustryRole, export-oriented cut flower production center]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: flowerIndustryRole Context triple: [Madrid, Cundinamarca, flowerIndustryRole, export-oriented cut flower production center]
-
A.
flowerType
Indicates the specific kind or category of flower associated with an entity.
-
B.
flowerStructure
Indicates the structural characteristics or organization of a flower, such as the arrangement and form of its parts.
-
C.
flowerSex
Indicates that one entity has a specified sexual characteristic or reproductive role in relation to a flower.
-
D.
hasFlowerColor
Indicates that an entity (typically a plant or flower) possesses a specific flower color.
-
E.
flowerCharacteristic
Indicates that a flower possesses a particular attribute, quality, or feature (such as color, shape, size, or scent).
- F. None of above. chosen
Provenance (4 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_69a8861acab88190bb43cde203429399 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aadb7bda1081908f2c41c520c9c55c |
completed | March 6, 2026, 1:49 p.m. |
| PD | Predicate disambiguation | batch_69aa61c0a0288190bce9d60062a84b69 |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69aadb68868c819097ec6db6194abae6 |
completed | March 6, 2026, 1:49 p.m. |
Created at: March 4, 2026, 7:30 p.m.