Triple
T151805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Time Warner |
E3446
|
entity |
| Predicate | owned |
P347
|
FINISHED |
| Object | CNN |
E10223
|
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: CNN | Statement: [Time Warner, owned, CNN]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CNN Context triple: [Time Warner, owned, CNN]
-
A.
CNN
chosen
CNN is a major American cable news television channel known for pioneering 24-hour news coverage and live reporting from global events.
-
B.
NBC
NBC is a major American broadcast television network known for its nationwide programming, including news, sports, and entertainment.
-
C.
NBC Nightly News
NBC Nightly News is a long-running American evening television news program that provides national and international news coverage on the NBC network.
-
D.
Fox News Channel
Fox News Channel is a major American cable television news network known for its conservative-leaning commentary and wide influence on U.S. political discourse.
-
E.
CBS
CBS is a major American broadcast television network known for airing a wide range of popular news, sports, and entertainment programming nationwide.
- 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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a2580f55a88190b37b54ee0ed5ac7c |
completed | Feb. 28, 2026, 2:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2c93bbd508190b81527bd95c6e5f4 |
completed | Feb. 28, 2026, 10:53 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.