Triple
T13564443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dann Florek |
E323995
|
entity |
| Predicate | hasActedIn |
P15620
|
FINISHED |
| Object | Wings |
E177171
|
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: Wings | Statement: [Dann Florek, hasActedIn, Wings]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wings Context triple: [Dann Florek, hasActedIn, Wings]
-
A.
Wings
chosen
Wings is an American sitcom that aired in the 1990s, centered on the lives and misadventures of staff at a small regional airline on Nantucket Island.
-
B.
Wings
"Wings" is a track from the Black Eyed Peas' concept album *Masters of the Sun Vol. 1*, blending hip hop with socially conscious themes.
-
C.
Wings
Wings is a 1927 silent World War I aviation film that became the first movie ever to win the Academy Award for Best Picture.
-
D.
Wings
Wings is a 1966 Soviet drama film directed by Larisa Shepitko that explores the postwar life and inner struggles of a former World War II fighter pilot turned school principal.
-
E.
Wings
Wings is a smokeless tobacco brand produced by the American Snuff Company.
- 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_69d8076830b48190910a902bae5888e2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb00bbe848190bb33efe2af528295 |
completed | April 12, 2026, 2:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f75daf1bfc8190bf22eb9ef242f54f |
completed | May 3, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:47 p.m.