Triple
T4764411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University Parks |
E105772
|
entity |
| Predicate | hasBotanicalInterest |
P59180
|
FINISHED |
| Object | trees |
—
|
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: trees | Statement: [University Parks, hasBotanicalInterest, trees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBotanicalInterest Context triple: [University Parks, hasBotanicalInterest, trees]
-
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.
hasBotanicalGarden
Indicates that one entity possesses, contains, or includes a botanical garden as part of its facilities or domain.
-
C.
hasHerbarium
Indicates that an entity possesses, is associated with, or maintains a herbarium collection.
-
D.
hasBotanicalGardenArea_ha
Indicates that an entity possesses a botanical garden whose area is measured in hectares.
-
E.
involvesPlant
Indicates that the relationship or action includes or pertains to a plant as a participating entity.
- 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_69bd43f14cac819081c7c69803648211 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd686ef1b08190ad60375592c9d6c0 |
completed | March 20, 2026, 3:31 p.m. |
| PD | Predicate disambiguation | batch_69bd622807f881908e4bcb14f7731bac |
completed | March 20, 2026, 3:05 p.m. |
| PDg | Predicate description generation | batch_69bd686dc7b88190b41e8a362701080d |
completed | March 20, 2026, 3:31 p.m. |
Created at: March 20, 2026, 1:21 p.m.