Triple
T6436239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ogasawara, Tokyo |
E129901
|
entity |
| Predicate | travelTimeByFerry |
P70601
|
FINISHED |
| Object | about 24 hours |
—
|
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 24 hours | Statement: [Ogasawara, Tokyo, travelTimeByFerry, about 24 hours]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelTimeByFerry Context triple: [Ogasawara, Tokyo, travelTimeByFerry, about 24 hours]
-
A.
hasFerryService
Indicates that there is an operational ferry connection or transport service available between the related locations or entities.
-
B.
hasFerryComponent
Indicates that something includes or is associated with a ferry-related part, feature, or segment within its structure or operation.
-
C.
hasFerryType
Indicates that an entity (such as a ferry route or service) is associated with a specific type or category of ferry.
-
D.
hasFerryPort
Indicates that a place serves as a location where ferries regularly dock to load and unload passengers or cargo.
-
E.
ferryRange
Indicates the maximum distance an aircraft can fly without payload or passengers, typically with full fuel, under specified conditions.
- 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_69c0084caac48190a7bc2ad8ba44536f |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c069622eb881908b40fc8079d312d6 |
completed | March 22, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69c060f96980819091bab9335922a457 |
completed | March 22, 2026, 9:36 p.m. |
| PDg | Predicate description generation | batch_69c0623e3cd48190929b0e3cba013909 |
completed | March 22, 2026, 9:42 p.m. |
Created at: March 22, 2026, 4:45 p.m.