Triple
T23436136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bad and Crazy |
E563465
|
entity |
| Predicate | originalNetwork |
P2594
|
FINISHED |
| Object | tvN |
—
|
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: tvN | Statement: [Bad and Crazy, originalNetwork, tvN]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: tvN Context triple: [Bad and Crazy, originalNetwork, tvN]
-
A.
tvN
chosen
tvN is a South Korean cable television network known for producing popular and critically acclaimed dramas, variety shows, and entertainment programs.
-
B.
TVING
TVING is a South Korean online streaming platform offering a wide range of domestic films, dramas, and entertainment content.
-
C.
TVN
TVN is Chile's main public television network, known for its nationwide news, entertainment, and cultural programming.
-
D.
JTBC
JTBC is a South Korean nationwide cable and satellite television network known for its high-quality dramas, news, and variety programming.
-
E.
MBC Dramia
MBC Dramia is a large historical drama filming set and tourist attraction in Yongin, South Korea, featuring full-scale replicas of traditional Korean palaces and villages used in popular TV series.
- 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_69e24553980c8190bb66a2ae0bdab125 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1a5dbdf248190a09e971f2718d01f |
completed | April 29, 2026, 6:31 a.m. |
Created at: April 17, 2026, 5:50 p.m.