Triple
T16179195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MG Cars |
E392642
|
entity |
| Predicate | notableModel |
P1503
|
FINISHED |
| Object | MG ZS |
E91031
|
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: MG ZS | Statement: [MG Cars, notableModel, MG ZS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MG ZS Context triple: [MG Cars, notableModel, MG ZS]
-
A.
MG ZS
chosen
The MG ZS is a compact crossover SUV produced under the MG marque, known for its value-focused pricing, practical interior, and popularity in markets such as the UK, Europe, and Asia.
-
B.
MG ZR
The MG ZR is a sporty compact hatchback produced by MG Rover in the early 2000s, known for its performance-oriented tuning and popularity in the hot hatch segment.
-
C.
MG ZT
The MG ZT is a performance-oriented executive saloon car produced by MG Rover in the early 2000s, known for its sporty handling and distinctive British styling.
-
D.
BMW X5
The BMW X5 is a mid-size luxury SUV known for combining strong performance, advanced technology, and upscale comfort in BMW’s X-series lineup.
-
E.
BMW X4
The BMW X4 is a compact luxury crossover SUV with coupe-like styling, positioned as a sportier alternative to the more traditional BMW X3.
- 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_69d87f1d32208190942e4e499a80c18c |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2205b88b481908ecdd8d663dc668b |
completed | April 17, 2026, 11:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fffefe4dc08190a6cc43a448ae6554 |
completed | May 10, 2026, 3:43 a.m. |
Created at: April 10, 2026, 5:02 a.m.