Triple
T37749640
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yufuin no Mori |
E940944
|
entity |
| Predicate | primaryDestinationType |
P142230
|
FINISHED |
| Object | hot spring resort town |
—
|
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: hot spring resort town | Statement: [Yufuin no Mori, primaryDestinationType, hot spring resort town]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryDestinationType Context triple: [Yufuin no Mori, primaryDestinationType, hot spring resort town]
-
A.
primaryDestinationsType
chosen
Indicates the type or category of main destinations associated with an entity or activity.
-
B.
primaryTargetType
Indicates the main category or type of entity that is the principal focus or intended recipient of an action, effect, or operation.
-
C.
primaryUSDestination
Indicates that an entity’s main or most significant destination within the United States is the specified location.
-
D.
primaryRouteType
Indicates the main category or kind of route associated with an entity, such as its primary mode, path, or routing classification.
-
E.
primaryType
Indicates the main or most fundamental category or classification assigned to an entity, distinguishing it from any secondary or auxiliary types.
- 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_69f76ee1f3a88190834e6c8af99bccc9 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a1772e48190ba738c6d11b321e2 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:19 p.m.