Triple
T10293833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mazda Motor Manufacturing USA plant |
E241431
|
entity |
| Predicate | closedAsMazdaJVYear |
P19867
|
FINISHED |
| Object | 1992 |
—
|
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: 1992 | Statement: [Mazda Motor Manufacturing USA plant, closedAsMazdaJVYear, 1992]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: closedAsMazdaJVYear Context triple: [Mazda Motor Manufacturing USA plant, closedAsMazdaJVYear, 1992]
-
A.
suspensionYear
Indicates the year in which a suspension (such as a ban, halt, or temporary discontinuation of activity) takes effect or is recorded.
-
B.
closureYear
chosen
Indicates the year in which an entity (such as an organization, facility, or service) ceased operations or was officially closed.
-
C.
lastAppearanceYear
Indicates the calendar year in which an entity made its most recent appearance.
-
D.
winnerModelYear
Indicates that a model was the winning model for a particular year.
-
E.
demonstrationYear
Indicates the year in which a demonstration, display, or public showing of something took place.
- 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.