Triple
T10105207
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Acton Arboretum |
E216300
|
entity |
| Predicate | hasPlantCollections |
P36488
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Acton Arboretum, hasPlantCollections, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPlantCollections Context triple: [Acton Arboretum, hasPlantCollections, yes]
-
A.
hasHerbarium
Indicates that an entity possesses, is associated with, or maintains a herbarium collection.
-
B.
plantCollection
chosen
Indicates that one entity maintains or possesses a collection of plants, typically grouped or curated as a set.
-
C.
hasBotanicalGarden
Indicates that one entity possesses, contains, or includes a botanical garden as part of its facilities or domain.
-
D.
hasPlantCategory
Indicates that one entity is assigned to, or classified under, a particular plant-related category or type.
-
E.
hasBotanicalInterest
Indicates that one entity has a particular interest or concern in the botanical characteristics, study, or cultivation of another entity.
- 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_69ca83d039f08190b9d10363221c69fb |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cdd09dde888190bb550a3cd0b204fe |
completed | April 2, 2026, 2:12 a.m. |
| PD | Predicate disambiguation | batch_69cd4b9b853c8190a2af993ce9b21309 |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9:03 p.m.