Triple
T4891879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nadi–Tokyo |
E109581
|
entity |
| Predicate | isNonstopPossible |
P60441
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Nadi–Tokyo, isNonstopPossible, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isNonstopPossible Context triple: [Nadi–Tokyo, isNonstopPossible, true]
-
A.
hasStopType
Indicates that a stop or stopping point is classified as having a particular type or category of stop.
-
B.
hasStop
Indicates that something (such as a route, service, or journey) includes or is associated with a particular stop or stopping point.
-
C.
hasStopFeature
Indicates that one entity possesses or is equipped with a feature that enables stopping or halting an associated process, action, or movement.
-
D.
isNonPeriodic
Indicates that the subject does not occur, repeat, or follow a pattern at regular intervals over time.
-
E.
hasStopNear
Indicates that one entity has a stop or stopping point located in close proximity to another entity.
- 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_69bd4410bbf88190aad50d2451c863d6 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ffabccc81909115ece1b04e2061 |
completed | March 20, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69bd6c2e7b5c8190b8bf9d616dfa24f0 |
completed | March 20, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69bd6ff731188190a9903602122d4ff9 |
completed | March 20, 2026, 4:04 p.m. |
Created at: March 20, 2026, 1:28 p.m.