Triple
T37749654
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yufuin no Mori |
E940944
|
entity |
| Predicate | targetPassengerType |
P138413
|
FINISHED |
| Object | tourists |
—
|
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: tourists | Statement: [Yufuin no Mori, targetPassengerType, tourists]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetPassengerType Context triple: [Yufuin no Mori, targetPassengerType, tourists]
-
A.
appliesToPassengerType
chosen
Indicates that a rule, condition, or attribute is relevant or restricted to a specific type or category of passenger.
-
B.
passengersType
Indicates the type or category of passengers associated with or involved in a given entity or context.
-
C.
isPassengerWith
Indicates that one entity is traveling together with another entity as a passenger in the same vehicle or conveyance.
-
D.
hasPassengerRole
Indicates that an entity participates in a context or event specifically in the capacity or role of a passenger.
-
E.
passengerLevel
Indicates the relative status, class, or priority assigned to a passenger within a transportation or service context.
- 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_69ff48199b1c8190bb05872f8a4f4673 |
completed | May 9, 2026, 2:43 p.m. |
| PD | Predicate disambiguation | batch_69ff4746b1cc8190854f70a124df7d04 |
completed | May 9, 2026, 2:40 p.m. |
Created at: May 3, 2026, 4:19 p.m.