Triple
T12274268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clásico Universitario |
E292549
|
entity |
| Predicate | mediaNameLanguage |
P41181
|
FINISHED |
| Object | Spanish-language sports media |
—
|
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: Spanish-language sports media | Statement: [Clásico Universitario, mediaNameLanguage, Spanish-language sports media]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mediaNameLanguage Context triple: [Clásico Universitario, mediaNameLanguage, Spanish-language sports media]
-
A.
mediaLanguage
Indicates the language in which a media item (such as a film, broadcast, or publication) is originally produced or presented.
-
B.
mediaName
chosen
Indicates the name or title assigned to a media item (such as a work, file, or publication) in the relationship.
-
C.
dominantMediaLanguage
Indicates that one language is the primary or most prevalent medium of communication used in a given media context or outlet.
-
D.
languageOfWorkOrName
Indicates the language in which a work is created or a name is expressed.
-
E.
languageSpokenOnScreen
Indicates that a particular language is used in spoken dialogue or audible communication within an on-screen work (such as a film, show, or video).
- 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_69d6ab6856488190b5d31178d5015f8e |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d9380a5e78819086bd4dfe9a83d1f5 |
completed | April 10, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69d91c4a66cc819083ce6fcaf5042af6 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:52 p.m.