Triple
T34263492
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meguro River cherry blossoms |
E879098
|
entity |
| Predicate | approximateViewingLength |
P198946
|
FINISHED |
| Object | about 3 to 4 kilometers |
—
|
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 3 to 4 kilometers | Statement: [Meguro River cherry blossoms, approximateViewingLength, about 3 to 4 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateViewingLength Context triple: [Meguro River cherry blossoms, approximateViewingLength, about 3 to 4 kilometers]
-
A.
typicalViewingTime
Indicates the usual or most common amount of time an entity is viewed or watched under normal circumstances.
-
B.
minimumViewingTime
Indicates the least amount of time an item must be viewed or played for a condition (such as completion, eligibility, or credit) to be considered satisfied.
-
C.
filmRuntimeApprox
Indicates an approximate or estimated duration of a film, rather than its exact runtime.
-
D.
approximateCourseLength
Indicates an estimated or rough value for the length or duration of a course rather than an exact measurement.
-
E.
lengthInMinutes
Indicates the duration of something expressed as a number of minutes.
- F. None of above. chosen
Provenance (4 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_69ff16775a9881909d26dbc1f0ef3e1c |
completed | May 9, 2026, 11:11 a.m. |
| PD | Predicate disambiguation | batch_69ff158e61708190a1c581d0d306cfce |
completed | May 9, 2026, 11:07 a.m. |
| PDg | Predicate description generation | batch_69ff167608f08190b7cd2cf65ddecbf3 |
completed | May 9, 2026, 11:11 a.m. |
Created at: May 1, 2026, 1:56 a.m.