Triple
T3831876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MG |
E91030
|
entity |
| Predicate | notableModel |
P1503
|
FINISHED |
| Object | MG3 |
E91030
|
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: MG3 | Statement: [MG, notableModel, MG3]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MG3 Context triple: [MG, notableModel, MG3]
-
A.
MG 3
The MG 3 is a German general-purpose machine gun developed in the post–World War II era, derived from the wartime MG 42 design and widely used by NATO and other armed forces.
-
B.
MG 1
MG 1 is a post–World War II German light machine gun developed as a modernized successor to the wartime MG 42, retaining its high rate of fire while adapting to NATO standards.
-
C.
MG
chosen
MG is a historic British automotive marque best known for its sports cars, now owned and produced by Chinese manufacturer SAIC Motor.
-
D.
MGY
MGY was the distinctive wireless call sign used by the RMS Titanic for its radio communications.
-
E.
MAG
MAG is a major British airport operator that owns and manages several UK airports, including Manchester Airport.
- 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_69aed960b538819096561c8ed448dec9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeeb8787bc8190819a7af975b609df |
completed | March 9, 2026, 3:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b512259d048190be25add7e38a0326 |
completed | March 14, 2026, 7:45 a.m. |
Created at: March 9, 2026, 3:17 p.m.