Triple
T2097736
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yu Garden |
E37019
|
entity |
| Predicate | hasPlanting |
P3806
|
FINISHED |
| Object | ornamental 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: ornamental trees | Statement: [Yu Garden, hasPlanting, ornamental trees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPlanting Context triple: [Yu Garden, hasPlanting, ornamental trees]
-
A.
involvesPlant
chosen
Indicates that the relationship or action includes or pertains to a plant as a participating entity.
-
B.
hasLandscaping
Indicates that an entity possesses or is associated with designed outdoor grounds or landscape features.
-
C.
isPlantOf
Indicates that one entity is a plant that belongs to, is associated with, or is characteristic of another entity (such as a region, habitat, or owner).
-
D.
hasSoil
Indicates that one entity possesses, contains, or is associated with a particular type or instance of soil.
-
E.
plantingStyle
Indicates the method or arrangement used to plant entities in relation to each other or their environment.
- 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_69a8861828948190924aa30c08806b3a |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abba9cb84481909fe0a66c020b8864 |
completed | March 7, 2026, 5:41 a.m. |
| PD | Predicate disambiguation | batch_69abb7b6274081909df36cd7a7c6a675 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:43 p.m.