Triple
T7217945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toyota RAV4 |
E150182
|
entity |
| Predicate | competitor |
P1375
|
FINISHED |
| Object | Mazda CX-5 |
E395831
|
NE 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: Mazda CX-5 | Statement: [Toyota RAV4, competitor, Mazda CX-5]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mazda CX-5 Context triple: [Toyota RAV4, competitor, Mazda CX-5]
-
A.
Mazda CX-5
chosen
The Mazda CX-5 is a compact crossover SUV known for its stylish design, engaging driving dynamics, and efficient Skyactiv technology.
-
B.
Mazda CX-30
The Mazda CX-30 is a compact crossover SUV known for its sleek design, upscale interior, and engaging driving dynamics within Mazda’s lineup.
-
C.
Mazda CX-9
The Mazda CX-9 is a mid-size three-row crossover SUV known for its stylish design, upscale interior, and engaging driving dynamics.
-
D.
Mazda3
The Mazda3 is a popular compact car known for its sporty handling, stylish design, and well-appointed interior.
-
E.
Mazda6
The Mazda6 is a mid-size family sedan known for its sporty handling, stylish design, and strong value in the mainstream car market.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c687effb44819092b95d07d0368c9f |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6e99170d88190b1aef326a7d81134 |
completed | March 27, 2026, 8:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7cbfb46388190992cc98039e71748 |
completed | March 28, 2026, 12:39 p.m. |
Created at: March 27, 2026, 2:53 p.m.