Triple
T3703531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parc de la Tête d’Or |
E80836
|
entity |
| Predicate | hasBotanicalCollection |
P36488
|
FINISHED |
| Object | tropical plants |
—
|
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: tropical plants | Statement: [Parc de la Tête d’Or, hasBotanicalCollection, tropical plants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBotanicalCollection Context triple: [Parc de la Tête d’Or, hasBotanicalCollection, tropical plants]
-
A.
hasBotanicalResource
Indicates that an entity possesses, contains, or is associated with a plant-based resource (such as plants, plant parts, or botanical materials) used for some purpose.
-
B.
hasHerbarium
Indicates that an entity possesses, is associated with, or maintains a herbarium collection.
-
C.
hasBotanicalGarden
Indicates that one entity possesses, contains, or includes a botanical garden as part of its facilities or domain.
-
D.
hasBotanicalGardenArea_ha
Indicates that an entity possesses a botanical garden whose area is measured in hectares.
-
E.
plantCollection
chosen
Indicates that one entity maintains or possesses a collection of plants, typically grouped or curated as a set.
- 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_69ad8b1793888190a5f70e4b21dc05a1 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adc54aaac88190b775dba2513b6d4a |
completed | March 8, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69adb84eeca48190bb4de637e9f0e27a |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:33 p.m.