Triple
T16179649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MG TF |
E392651
|
entity |
| Predicate | relatedModel |
P37
|
FINISHED |
| Object | MG TD |
E392650
|
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 TD | Statement: [MG TF, relatedModel, MG TD]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MG TD Context triple: [MG TF, relatedModel, MG TD]
-
A.
MG TD
chosen
The MG TD is a classic British two-seat roadster produced in the early 1950s, renowned for popularizing the sports car concept in the United States with its nimble handling and traditional open-top design.
-
B.
MG TC
The MG TC is a classic British two-seat sports car produced just after World War II that helped popularize the sports car concept, especially in the United States.
-
C.
MG TF
The MG TF is a small British two-seat sports car produced by MG, known for its agile handling and classic roadster styling.
-
D.
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.
-
E.
Magaro
Magaro is an Italian-origin surname most notably borne by American actor John Magaro.
- 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_69d87f1e49ac8190a311b54d32990576 |
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_6a0025f183d88190b269233ff6e65d75 |
completed | May 10, 2026, 6:30 a.m. |
Created at: April 10, 2026, 5:02 a.m.