Triple
T19868259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MGM+ |
E477446
|
entity |
| Predicate | contentSource |
P409
|
FINISHED |
| Object | MGM film library |
—
|
NE NERFINISHED |
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: MGM film library | Statement: [MGM+, contentSource, MGM film library]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MGM film library Context triple: [MGM+, contentSource, MGM film library]
-
A.
MGM film library
chosen
The MGM film library is a vast collection of classic movies and television content originally produced or distributed by Metro-Goldwyn-Mayer, encompassing many of Hollywood’s most iconic titles.
-
B.
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.
-
C.
MGM
MGM is the three-letter National Rail station code assigned to Metheringham railway station in Lincolnshire, England.
-
D.
MGM
MGM is the three-letter FAA location identifier assigned to Harbor Springs Municipal Airport in Michigan.
-
E.
MGM
MGM is a major American entertainment and hospitality brand best known for its iconic casinos, resorts, and film studio legacy.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e51e7d948190aedbcd6c30361c39 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e658a168288190a2fbb735d1fd30a8 |
completed | April 20, 2026, 4:47 p.m. |
Created at: April 10, 2026, 1:51 p.m.