Triple
T20007582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Sexta |
E494497
|
entity |
| Predicate | sisterChannel |
P5818
|
FINISHED |
| Object | Nova |
—
|
NE NERFINISHED |
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: Nova | Statement: [La Sexta, sisterChannel, Nova]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nova Context triple: [La Sexta, sisterChannel, Nova]
-
A.
Nova
Nova is a highly skilled Terran Ghost operative and elite sniper from the StarCraft universe, known for her stealth, psionic abilities, and central role in various StarCraft stories and missions.
-
B.
Nova
chosen
Nova is a Spanish television channel that primarily targets female audiences with a mix of telenovelas, lifestyle programs, and entertainment content.
-
C.
Nova
Nova is a music producer known for crafting the sound of the track "Crime Pays."
-
D.
Nova
Nova is the name given to TransPennine Express’s modern fleet of intercity trains used across its key routes in the North of England and Scotland.
-
E.
Nova
Nova is the OpenStack project that provides scalable, on-demand compute resources for running virtual machines and other instances in cloud environments.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da626b2d748190886981ea90c8b2ea |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e661a648a88190853ee741edcf6ca2 |
completed | April 20, 2026, 5:25 p.m. |
Created at: April 11, 2026, 3:33 p.m.