Triple
T19841820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nissan Oppama Plant |
E476751
|
entity |
| Predicate | product |
P490
|
FINISHED |
| Object |
Nissan Cube
The Nissan Cube is a compact, box-shaped car known for its quirky asymmetrical design and spacious, practical interior.
|
E1398823
|
NE FINISHED |
How this triple was built (4 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: Nissan Cube | Statement: [Nissan Oppama Plant, product, Nissan Cube]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nissan Cube Context triple: [Nissan Oppama Plant, product, Nissan Cube]
-
A.
Nissan Latio
The Nissan Latio is a subcompact sedan produced by Nissan, marketed in various regions as a practical, fuel-efficient family car.
-
B.
Nissan Kubistar
The Nissan Kubistar is a compact light commercial van produced by Nissan, essentially a rebadged version of the first-generation Renault Kangoo for certain European markets.
-
C.
Nissan Micra
The Nissan Micra is a long-running subcompact hatchback car known for its small size, fuel efficiency, and popularity in urban markets worldwide.
-
D.
Azuga
Azuga is a small mountain resort town in Romania known for its ski slopes and scenic location in the Carpathian Mountains.
-
E.
Nissan Juke
The Nissan Juke is a subcompact crossover SUV known for its distinctive, unconventional styling and sporty driving character.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Nissan Cube Triple: [Nissan Oppama Plant, product, Nissan Cube]
Generated description
The Nissan Cube is a compact, box-shaped car known for its quirky asymmetrical design and spacious, practical interior.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nissan Cube Target entity description: The Nissan Cube is a compact, box-shaped car known for its quirky asymmetrical design and spacious, practical interior.
-
A.
Nissan Latio
The Nissan Latio is a subcompact sedan produced by Nissan, marketed in various regions as a practical, fuel-efficient family car.
-
B.
Nissan Kubistar
The Nissan Kubistar is a compact light commercial van produced by Nissan, essentially a rebadged version of the first-generation Renault Kangoo for certain European markets.
-
C.
Nissan Micra
The Nissan Micra is a long-running subcompact hatchback car known for its small size, fuel efficiency, and popularity in urban markets worldwide.
-
D.
Azuga
Azuga is a small mountain resort town in Romania known for its ski slopes and scenic location in the Carpathian Mountains.
-
E.
Nissan Juke
The Nissan Juke is a subcompact crossover SUV known for its distinctive, unconventional styling and sporty driving character.
- F. None of above. chosen
Provenance (5 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_69d8e51d39d081909bcfafeaaf3d2fcc |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65806375c8190a4f45f14aeb06515 |
completed | April 20, 2026, 4:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07d438c0208190a6d5b6781b99d37e |
completed | May 16, 2026, 2:19 a.m. |
| NEDg | Description generation | batch_6a07d8082bfc81909db58a0477c4d55f |
completed | May 16, 2026, 2:35 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07d8744bdc8190adfcc428ff55e790 |
completed | May 16, 2026, 2:37 a.m. |
Created at: April 10, 2026, 1:51 p.m.