Triple
T4775976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MSG Network |
E106046
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | MSG |
E83474
|
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: MSG | Statement: [MSG Network, abbreviation, MSG]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MSG Context triple: [MSG Network, abbreviation, MSG]
-
A.
MSG
chosen
MSG is a famous multi-purpose indoor arena in New York City known for hosting major sports events, concerts, and entertainment spectacles.
-
B.
MSG
MSG is a subregional political and economic organization that promotes cooperation and solidarity among Melanesian countries and territories in the Pacific.
-
C.
MSG
MSG refers to U.S. Marine Security Guards, specialized Marine Corps personnel assigned to protect American embassies, consulates, and other diplomatic facilities worldwide.
-
D.
MSGS
MSGS is the stock ticker symbol for Madison Square Garden Sports Corp., a publicly traded company that owns and operates professional sports franchises and related entertainment assets.
-
E.
Messages
Messages is Apple’s built-in messaging app for iOS, iPadOS, and macOS that supports SMS, MMS, and iMessage communication across Apple devices.
- 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_69bd43f3074c8190937e7b0a457fe9f1 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6585bf088190a7847241c8868bf6 |
completed | March 20, 2026, 3:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be43c6d7848190b998eee680149d6f |
completed | March 21, 2026, 7:07 a.m. |
Created at: March 20, 2026, 1:21 p.m.