Triple
T17367691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Subaru Forester |
E422225
|
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: [Subaru Forester, competitor, Mazda CX-5]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mazda CX-5 Context triple: [Subaru Forester, 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-3
The Mazda CX-3 is a subcompact crossover SUV known for its sporty handling, stylish design, and fuel-efficient Skyactiv powertrain.
-
C.
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.
-
D.
Mazda CX-50 (in some markets/segments)
The Mazda CX-50 is a compact crossover SUV positioned as a more rugged, adventure-oriented companion to Mazda’s CX-5, featuring bolder styling and enhanced off-road capability for certain markets.
-
E.
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.
- 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_69d889d6535c81908be333c01deaec4e |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a661fc08190a4c386125bddb16b |
completed | April 19, 2026, 2:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a019566da6c819083b59e0911d02bd5 |
completed | May 11, 2026, 8:37 a.m. |
Created at: April 10, 2026, 5:44 a.m.