Triple
T20558491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vanessa Abrams |
E504782
|
entity |
| Predicate | network |
P2637
|
FINISHED |
| Object | The CW |
—
|
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: The CW | Statement: [Vanessa Abrams, network, The CW]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The CW Context triple: [Vanessa Abrams, network, The CW]
-
A.
The CW
chosen
The CW is an American broadcast television network known for targeting younger audiences with series in genres like teen drama, superhero shows, and fantasy.
-
B.
The WB
The WB was an American broadcast television network that operated from 1995 to 2006, best known for its lineup of youth-oriented dramas and genre series.
-
C.
WIN Television network
WIN Television network is a major Australian regional commercial television broadcaster that operates a network of stations affiliated with national networks to serve audiences outside the metropolitan markets.
-
D.
CBS
CBS is a premier undergraduate college of the University of Delhi specializing in business, management, and computer science education.
-
E.
CBS
CBS is a leading Danish university in Copenhagen specializing in business and economics education and research.
- 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_69e0b4b6587c8190aee63dc7cff244ea |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a5df84088190848c7eb35564d8f9 |
completed | April 20, 2026, 10:17 p.m. |
Created at: April 16, 2026, 11:38 a.m.