Triple
T13760960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wolseley Viper |
E330605
|
entity |
| Predicate | configuration |
P2093
|
FINISHED |
| Object | V8 |
E386317
|
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: V8 | Statement: [Wolseley Viper, configuration, V8]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: V8 Context triple: [Wolseley Viper, configuration, V8]
-
A.
V8
chosen
V8 is an eight-cylinder internal combustion engine configuration arranged in two banks of four cylinders forming a "V" shape, commonly used in high-performance and large vehicles.
-
B.
V8
V8 is Google’s high-performance open-source JavaScript engine, used in Chrome and Node.js to compile and execute JavaScript directly to native machine code.
-
C.
V8
V8 is a popular vegetable-based juice brand known for its blended vegetable and fruit beverages marketed as a nutritious drink option.
-
D.
Rhino JavaScript engine
Rhino JavaScript engine is an open-source JavaScript implementation written in Java that runs on the JVM and is used to execute JavaScript code within Java-based environments.
-
E.
Nashorn
Nashorn was a German World War II tank destroyer armed with a powerful 88 mm gun and built on a modified Panzer IV chassis.
- 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_69d81c573f288190aa2403d484fa3d49 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02250f4881908d5193b3d5d25844 |
completed | April 14, 2026, 9 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7a8606dbc8190b0f7c38583986141 |
completed | May 3, 2026, 7:56 p.m. |
Created at: April 9, 2026, 10:09 p.m.