Triple
T10293846
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mazda Motor Manufacturing USA plant |
E241431
|
entity |
| Predicate | transportModeForOutput |
P44050
|
FINISHED |
| Object | rail |
—
|
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: rail | Statement: [Mazda Motor Manufacturing USA plant, transportModeForOutput, rail]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transportModeForOutput Context triple: [Mazda Motor Manufacturing USA plant, transportModeForOutput, rail]
-
A.
transportModePresent
Indicates that a particular mode of transportation is involved or available in the described context or event.
-
B.
transportModeImportant
Indicates that the mode of transport used is considered significant or plays an important role in the context of the relationship or action.
-
C.
transportModeDesigned
Indicates that one entity is a mode of transport specifically designed or intended for use by another entity.
-
D.
transportModeFamily
chosen
Indicates the general category or family of transportation mode to which a specific transport mode belongs (e.g., road, rail, air, water).
-
E.
publicTransitMode
Indicates the type of public transportation (e.g., bus, train, subway) used or associated with a given trip or segment.
- 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2d46fb08190b7694290692e47dc |
completed | April 7, 2026, 9:48 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f35e548190be3b4d92d65d2d20 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:42 a.m.