Triple
T177865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TNT |
E3614
|
entity |
| Predicate | sisterChannel |
P5818
|
FINISHED |
| Object | truTV |
E3615
|
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: truTV | Statement: [TNT, sisterChannel, truTV]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: truTV Context triple: [TNT, sisterChannel, truTV]
-
A.
truTV
chosen
truTV is an American cable television channel owned by Warner Bros. Discovery, best known for reality-based programming, comedy, and live sports coverage including NCAA March Madness games.
-
B.
TR
TR is the two-letter ISO 3166-1 alpha-2 country code assigned to Turkey for international standardization and referencing.
-
C.
YouTube TV
YouTube TV is a subscription-based live TV streaming service that offers access to major broadcast and cable channels over the internet.
-
D.
TW
TW is the two-letter ISO 3166 country code assigned to Taiwan (commonly referred to as Chinese Taipei in certain international contexts).
-
E.
HLN
HLN is an American cable news channel, originally launched as CNN Headline News, that focuses on concise news updates and true-crime 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_69a25374990081909766d30c79a18e0e |
completed | Feb. 28, 2026, 2:31 a.m. |
| NER | Named-entity recognition | batch_69a25bafd5808190a0a0cb2b21ce007f |
completed | Feb. 28, 2026, 3:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2fa7c7a288190bc547d5e7010732b |
completed | Feb. 28, 2026, 2:23 p.m. |
Created at: Feb. 28, 2026, 2:39 a.m.