Triple
T27152535
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amanohashidate |
E682428
|
entity |
| Predicate | hasApproximateNumberOfPineTrees |
P25753
|
FINISHED |
| Object | about 8000 |
—
|
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: about 8000 | Statement: [Amanohashidate, hasApproximateNumberOfPineTrees, about 8000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateNumberOfPineTrees Context triple: [Amanohashidate, hasApproximateNumberOfPineTrees, about 8000]
-
A.
numberOfTrees
chosen
Indicates the count or quantity of trees associated with a given entity or context.
-
B.
hasTrees
Indicates that something possesses or contains one or more trees.
-
C.
isForested
Indicates that an area or region is covered predominantly by forest or dense tree vegetation.
-
D.
hasApproximateNumberOfHills
Indicates that an entity is associated with an estimated or imprecise count of hills rather than an exact number.
-
E.
hasForestType
Indicates that an area or location is characterized by a specific type or classification of forest.
- 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_69eefaceb2a08190b9659b7f730629f5 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f6e6029a10819098ff21f58079e70e |
completed | May 3, 2026, 6:06 a.m. |
| PD | Predicate disambiguation | batch_69f6e3d5e8188190b1e1c2e5d1b77031 |
completed | May 3, 2026, 5:57 a.m. |
Created at: April 27, 2026, 9:15 a.m.