Triple
T34263491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meguro River cherry blossoms |
E879098
|
entity |
| Predicate | approximateTreeCount |
P25753
|
FINISHED |
| Object | several hundred 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: several hundred trees | Statement: [Meguro River cherry blossoms, approximateTreeCount, several hundred trees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateTreeCount Context triple: [Meguro River cherry blossoms, approximateTreeCount, several hundred trees]
-
A.
numberOfTrees
chosen
Indicates the count or quantity of trees associated with a given entity or context.
-
B.
hasApproximateLeaves
Indicates that one entity possesses a number of leaves that is approximately equal to the number of leaves of another entity.
-
C.
prototypeCountApproximate
Indicates that the number of prototypes involved is an estimated or approximate count rather than an exact value.
-
D.
mineCountApproximate
Indicates that the number of mines associated with an entity is estimated or roughly counted rather than known exactly.
-
E.
approximateBatCount
Indicates an estimated number of bats associated with or observed at a given entity or event.
- 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_69f349b421cc8190b4b4655e1d612548 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff14d596e88190be5263b7f96a96cd |
completed | May 9, 2026, 11:04 a.m. |
| PD | Predicate disambiguation | batch_69ff13f0208081909369aeb3b77a6b1f |
completed | May 9, 2026, 11:01 a.m. |
Created at: May 1, 2026, 1:56 a.m.