Triple
T23793485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nachi no Taki |
E588469
|
entity |
| Predicate | numberOfMainDrops |
P5954
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Nachi no Taki, numberOfMainDrops, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMainDrops Context triple: [Nachi no Taki, numberOfMainDrops, 1]
-
A.
hasNumberOfDrops
chosen
Indicates the quantity or count of drops associated with an entity or event.
-
B.
numberOfMainEvents
Indicates the total count of primary or most significant events associated with a given entity or context.
-
C.
numberOfMajorFalls
Indicates the count of significant or serious falling incidents experienced by an entity within a specified period or context.
-
D.
dropsFrom
Indicates that one entity falls, descends, or is released from another entity as its source or origin.
-
E.
largestSingleDrop
Indicates that one entity represents the greatest individual decrease (or loss) in a specified quantity relative to all comparable entities or time periods.
- 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_69e25d15db58819092ac1e6791696fd9 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c6da693481908194cbc9d6a0bfef |
completed | April 29, 2026, 8:52 a.m. |
| PD | Predicate disambiguation | batch_69f155fe300481909bd617443228df65 |
completed | April 29, 2026, 12:51 a.m. |
Created at: April 17, 2026, 7:41 p.m.