Triple
T13640754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coming Up |
E325968
|
entity |
| Predicate | artist |
P184
|
FINISHED |
| Object | Wings |
E43654
|
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: [Coming Up, artist, Wings]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wings Context triple: [Coming Up, artist, Wings]
-
A.
Wings
chosen
Wings was a British-American rock band formed by Paul McCartney after The Beatles, known for hits like "Band on the Run" and "Live and Let Die."
-
B.
Wings
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.
-
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 pop song by Australian singer-songwriter Delta Goodrem, known for its uplifting lyrics and powerful vocal performance.
- 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_69d8076beddc8190a53156f5bea77f5e |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc5aac7308190a3fd26baeade8f2a |
completed | April 12, 2026, 4:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f78af46fe481909c6f9a6f58f887d1 |
completed | May 3, 2026, 5:50 p.m. |
Created at: April 9, 2026, 9:51 p.m.