Triple
T26657911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maryland Lottery |
E666559
|
entity |
| Predicate | hasMediaChannel |
P131912
|
FINISHED |
| Object | televised drawings |
—
|
LITERAL 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: televised drawings | Statement: [Maryland Lottery, hasMediaChannel, televised drawings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMediaChannel Context triple: [Maryland Lottery, hasMediaChannel, televised drawings]
-
A.
hasMediaOutlet
Indicates that one entity possesses, controls, or is associated with a media outlet (such as a newspaper, TV channel, or online news platform).
-
B.
hasMediaHub
Indicates that one entity possesses, contains, or is associated with a central platform or facility for managing, distributing, or accessing media content.
-
C.
hasCanalOrChannel
Indicates that one entity possesses, contains, or is traversed by a canal or channel that serves as a conduit or passageway.
-
D.
hasCommonMedia
Indicates that two entities share at least one media item (such as an image, video, or audio file) in common.
-
E.
hasTelevisionChannelBrand
chosen
Indicates that an entity is associated with or operates under a particular television channel brand.
- F. None of above.
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_69ee9cf8c7188190b9b00270a8a89164 |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f71996e1a48190ac59a1d66d7c44e8 |
completed | May 3, 2026, 9:47 a.m. |
| PD | Predicate disambiguation | batch_69f71820c6c88190ab38b4fa626d22cc |
completed | May 3, 2026, 9:40 a.m. |
Created at: April 27, 2026, 2:35 a.m.