Triple
T289227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shrewsbury Flower Show |
E5952
|
entity |
| Predicate | hasTypeOfExhibitor |
P3517
|
FINISHED |
| Object | nurseries |
—
|
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: nurseries | Statement: [Shrewsbury Flower Show, hasTypeOfExhibitor, nurseries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfExhibitor Context triple: [Shrewsbury Flower Show, hasTypeOfExhibitor, nurseries]
-
A.
usedByExhibitorType
chosen
Indicates that something is utilized or applied by a specific type or category of exhibitor.
-
B.
hasExhibition
Indicates that an entity organizes, hosts, or presents a particular exhibition.
-
C.
hasExhibits
Indicates that an entity (such as a museum, gallery, or event) displays or presents certain items, artworks, or objects as part of its collection or show.
-
D.
hasMuseumType
Indicates that an entity is classified as a museum of a specific type or category.
-
E.
exhibitionType
Indicates the specific category or kind of exhibition associated with an entity (e.g., art show, trade fair, scientific exhibit).
- 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_69a25946a7ac8190a78871c210213272 |
completed | Feb. 28, 2026, 2:56 a.m. |
| NER | Named-entity recognition | batch_69a25e4df5508190ab75115ac6b3964e |
completed | Feb. 28, 2026, 3:17 a.m. |
| PD | Predicate disambiguation | batch_69a25b7d089081909810442c3d0182f6 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 3:02 a.m.