Triple
T2534603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GMA Network |
E56238
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | GMA-7 |
E56238
|
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: GMA-7 | Statement: [GMA Network, alsoKnownAs, GMA-7]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GMA-7 Context triple: [GMA Network, alsoKnownAs, GMA-7]
-
A.
GMA Network
chosen
GMA Network is a major Philippine commercial television and radio broadcasting company known for its nationwide reach and popular entertainment and news programs.
-
B.
TV5 Network
TV5 Network is a major Philippine television and media company known for its free-to-air channel TV5 and various entertainment, news, and sports programming.
-
C.
WGN-TV
WGN-TV is a Chicago-based television station and former national superstation known for its local news, sports broadcasts, and syndicated programming.
-
D.
ABS-CBN Corporation
ABS-CBN Corporation is a major Philippine media and entertainment conglomerate known for its television, radio, film, and digital content.
-
E.
WGN America
WGN America is a U.S.-based cable television network known for airing syndicated series, movies, and original programming to a national audience.
- 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_69ab4a49b6508190bc467fbef4bac334 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd27c8650819080005869789b802c |
completed | March 7, 2026, 7:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af2bbc416c81908774782420b54664 |
completed | March 9, 2026, 8:21 p.m. |
Created at: March 6, 2026, 9:47 p.m.