Triple
T3832308
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HMC |
E91040
|
entity |
| Predicate | hasUnderlyingCompanyBrand |
P27763
|
FINISHED |
| Object | Acura |
E91036
|
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: Acura | Statement: [HMC, hasUnderlyingCompanyBrand, Acura]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Acura Context triple: [HMC, hasUnderlyingCompanyBrand, Acura]
-
A.
Acura
chosen
Acura is Honda's luxury vehicle division, known for producing premium cars and SUVs with a focus on performance, technology, and reliability.
-
B.
Lexus
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.
-
C.
Infiniti
Infiniti is Nissan's luxury vehicle division, known for producing premium performance-oriented cars and SUVs.
-
D.
Honda
Honda is a historic Colombian river port city on the Magdalena River, known for its colonial architecture and numerous bridges.
-
E.
Honda
Honda is a major Japanese automobile and motorcycle manufacturer known for its reliable, fuel-efficient vehicles and global market presence.
- 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_69aed960b538819096561c8ed448dec9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeeb8787bc8190819a7af975b609df |
completed | March 9, 2026, 3:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b503fcddb481909690b708754d3d8a |
completed | March 14, 2026, 6:45 a.m. |
Created at: March 9, 2026, 3:17 p.m.