Triple
T2271116
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lexus LX |
E50659
|
entity |
| Predicate | manufacturer |
P490
|
FINISHED |
| Object | Lexus |
E167735
|
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: Lexus | Statement: [Lexus LX, manufacturer, Lexus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lexus Context triple: [Lexus LX, manufacturer, Lexus]
-
A.
Lexus
chosen
Lexus is the luxury vehicle division of the Japanese automaker Toyota, known for its premium sedans, SUVs, and hybrids that emphasize comfort, reliability, and advanced technology.
-
B.
Infiniti
Infiniti is Nissan's luxury vehicle division, known for producing premium performance-oriented cars and SUVs.
-
C.
Acura
Acura is Honda's luxury vehicle division, known for producing premium cars and SUVs with a focus on performance, technology, and reliability.
-
D.
Cadillac
Cadillac is a luxury automobile brand known for its premium vehicles and long-standing association with American upscale motoring.
-
E.
Nissan
Nissan is a major Japanese automobile manufacturer known for producing a wide range of passenger cars, trucks, and electric vehicles sold globally.
- 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_69a88b05910c8190a9a2b1ff230c85f9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc1c0de488190876b644cdaa41637 |
completed | March 7, 2026, 6:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae71db927c8190a76cfb873039b04b |
completed | March 9, 2026, 7:08 a.m. |
Created at: March 4, 2026, 7:48 p.m.