Triple
T34771499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokyo–Nagoya maglev line |
E1002373
|
entity |
| Predicate | projectedImpact |
P103390
|
FINISHED |
| Object | dramatically reduced travel time between Tokyo and Nagoya |
—
|
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: dramatically reduced travel time between Tokyo and Nagoya | Statement: [Tokyo–Nagoya maglev line, projectedImpact, dramatically reduced travel time between Tokyo and Nagoya]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: projectedImpact Context triple: [Tokyo–Nagoya maglev line, projectedImpact, dramatically reduced travel time between Tokyo and Nagoya]
-
A.
exportImpact
Indicates the effect or consequences that an entity’s exports have on another entity, system, or context.
-
B.
impactDescription
chosen
Indicates a description of the effect, consequence, or influence that one entity, action, or event has on another.
-
C.
recognizesImpactOn
Indicates that one entity acknowledges or understands the effect or consequences it has on another entity or situation.
-
D.
impactCategory
Indicates the type or domain of effect that one entity or action has on another, classifying the nature of its impact.
-
E.
timeHorizonOfImpact
Indicates the span of time over which an action, event, or factor is expected to produce its effects or consequences.
- 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_69f76db20dac8190b1e8d0ca4dc1d59f |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f7817daf00819098936402e75ab0a6 |
completed | May 3, 2026, 5:10 p.m. |
| PD | Predicate disambiguation | batch_69f780fc5ed88190b7200ee5a29940af |
completed | May 3, 2026, 5:08 p.m. |
Created at: May 3, 2026, 3:59 p.m.