Triple
T12668547
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sara Haines |
E302618
|
entity |
| Predicate | knownFor |
P22
|
FINISHED |
| Object | GMA Day |
E492044
|
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 Day | Statement: [Sara Haines, knownFor, GMA Day]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GMA Day Context triple: [Sara Haines, knownFor, GMA Day]
-
A.
GMA Day
chosen
GMA Day was a daytime talk show spin-off of ABC’s Good Morning America that served as the predecessor to Strahan, Sara and Keke.
-
B.
GMA 7 Manila
GMA 7 Manila is a flagship television station of GMA Network in Metro Manila, known for its wide-reaching news, public affairs, and entertainment programming in the Philippines.
-
C.
GMA Network Center
GMA Network Center is the main headquarters and broadcast complex of GMA Network in Quezon City, Philippines, housing its television, radio, and film production operations.
-
D.
24 Oras
24 Oras is a flagship Philippine television newscast known for delivering national and international news, public affairs reports, and special coverage on GMA Network.
-
E.
GMA News TV
GMA News TV is a Philippine free-to-air television network known for its news, public affairs, and informational programming.
- 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_69d7bded71a88190bb76e2413af9ea66 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96181c40481908f3e2717f5472b85 |
completed | April 10, 2026, 8:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6688bfc048190970d281e66c34cdc |
completed | May 2, 2026, 9:11 p.m. |
Created at: April 9, 2026, 5:20 p.m.