Triple
T889171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maryland General Assembly |
E19199
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object | MGA |
E19199
|
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: MGA | Statement: [Maryland General Assembly, hasAbbreviation, MGA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MGA Context triple: [Maryland General Assembly, hasAbbreviation, MGA]
-
A.
MGA
chosen
MGA is the commonly used abbreviation for the Maryland General Assembly, the state’s bicameral legislative body.
-
B.
MG
MG is a historic British automotive marque best known for its sports cars, now owned and produced by Chinese manufacturer SAIC Motor.
-
C.
MGM
MGM (Metro-Goldwyn-Mayer) is a historic American film studio renowned for its iconic roaring lion logo and for producing many of the most famous movies of Hollywood’s Golden Age.
-
D.
MICA Entertainment
MICA Entertainment is a film production company known for helping finance and produce feature films such as the historical adventure drama "The Lost City of Z."
-
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_69a4939d37188190848be3d426ebc9ae |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4acff52008190ac2975c08ad29f54 |
completed | March 1, 2026, 9:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7c023464481909759c457e87266ab |
completed | March 4, 2026, 5:16 a.m. |
Created at: March 1, 2026, 7:39 p.m.