Triple
T21146144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fairlady Z (Z34) |
E521058
|
entity |
| Predicate | marketSpecificName |
P69256
|
FINISHED |
| Object | Japan-only Fairlady Z badging |
—
|
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: Japan-only Fairlady Z badging | Statement: [Fairlady Z (Z34), marketSpecificName, Japan-only Fairlady Z badging]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marketSpecificName Context triple: [Fairlady Z (Z34), marketSpecificName, Japan-only Fairlady Z badging]
-
A.
marketingNameOf
Indicates that one entity is the marketing or brand name used to promote or refer to another entity.
-
B.
countrySpecificName
Indicates that an entity has a name or label that is specific to, or used within, a particular country.
-
C.
marketNameInUnitedStates
Indicates that an entity’s name or designation as used in the United States market is being specified.
-
D.
resolutionMarketingName
Indicates the marketed or consumer-facing name used to describe a product’s resolution.
-
E.
marketNameInJapan
chosen
Indicates the specific name under which a product, brand, or entity is marketed in Japan.
- 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_69e0b50c6a848190a4e525a77a319b8a |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e723fdc25481909d6648e09b069c41 |
completed | April 21, 2026, 7:15 a.m. |
| PD | Predicate disambiguation | batch_69e5f5f8a5bc819081918c7fa8e4496d |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 2:58 p.m.