Triple
T15064156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Vow |
E379711
|
entity |
| Predicate | starredActor |
P5563
|
FINISHED |
| Object | Channing Tatum |
E260476
|
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: Channing Tatum | Statement: [The Vow, starredActor, Channing Tatum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Channing Tatum Context triple: [The Vow, starredActor, Channing Tatum]
-
A.
Channing Tatum
chosen
Channing Tatum is an American actor and producer known for his roles in films such as "Magic Mike," "21 Jump Street," and various action and comedy movies.
-
B.
Bob Cummings
Bob Cummings was an American actor and television star best known for his charming comedic roles in film and early TV sitcoms such as "The Bob Cummings Show."
-
C.
Luke Evans
Luke Evans is a Welsh actor and singer known for his roles in films such as "The Hobbit" trilogy, "Dracula Untold," and various high-profile Hollywood productions.
-
D.
Adam Beach
Adam Beach is a Canadian First Nations actor known for his roles in films such as "Smoke Signals," "Windtalkers," and "Flags of Our Fathers," as well as various television series.
-
E.
Joe Manganiello
Joe Manganiello is an American actor known for roles in projects like "True Blood," "Magic Mike," and various action films.
- 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_69d85cd7683881908d405c1b5d7b4f7f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69dedee803ac81908bb7d66e49c2eb72 |
completed | April 15, 2026, 12:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fea5c8b3ac8190b8fc921b6e6eeed5 |
completed | May 9, 2026, 3:11 a.m. |
Created at: April 10, 2026, 3:02 a.m.