Triple
T6070354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shishinden |
E135264
|
entity |
| Predicate | hasAssociatedTree |
P6706
|
FINISHED |
| Object | tachibana tree (on the right side) |
—
|
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: tachibana tree (on the right side) | Statement: [Shishinden, hasAssociatedTree, tachibana tree (on the right side)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAssociatedTree Context triple: [Shishinden, hasAssociatedTree, tachibana tree (on the right side)]
-
A.
hasTree
chosen
Indicates that one entity possesses, contains, or is associated with a tree.
-
B.
hasOfficialStateTree
Indicates that a political entity has a designated tree recognized as its official state symbol.
-
C.
hasAssociatedPosition
Indicates that one entity is linked to a specific role, job, or spatial/organizational position associated with it.
-
D.
hasSurroundingTreeCommonName
Indicates that an entity is associated with a surrounding tree identified by its common (vernacular) name.
-
E.
hasTrees
Indicates that something possesses or contains one or more trees.
- 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_69c00879e8048190b690717d19c5bc03 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05742867481908e3f45c875807c73 |
completed | March 22, 2026, 8:55 p.m. |
| PD | Predicate disambiguation | batch_69c049f21fe08190995df3c5c05fb8ea |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:10 p.m.