Triple
T19262478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Columbia Road Flower Market |
E481681
|
entity |
| Predicate | typicalProductCategory |
P90900
|
FINISHED |
| Object | cut flowers |
—
|
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: cut flowers | Statement: [Columbia Road Flower Market, typicalProductCategory, cut flowers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalProductCategory Context triple: [Columbia Road Flower Market, typicalProductCategory, cut flowers]
-
A.
typeOfProducts
chosen
Indicates the kinds or categories of products that are associated with or offered by an entity.
-
B.
commonUseCategory
Indicates that multiple entities share the same general category of use or functional purpose.
-
C.
productionCategory
Indicates the classification or type of production process, output, or activity that an entity is associated with.
-
D.
typicalProductionType
Indicates the usual or characteristic type of production activity associated with an entity.
-
E.
apparentCategory
Indicates the category or type that something seems to belong to based on its observable characteristics, regardless of its true or underlying classification.
- 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_69d8e8ce54cc8190998418ff1f66ef28 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fb8ac1a8819094309db4a2e6b163 |
completed | April 20, 2026, 10:10 a.m. |
| PD | Predicate disambiguation | batch_69e4dd07a7208190afcd51ba1dc87c33 |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:28 p.m.