Triple
T10036729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Larisa Shepitko |
E205188
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
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.
|
E837331
|
NE FINISHED |
How this triple was built (4 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: [Larisa Shepitko, notableWork, Wings]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wings Context triple: [Larisa Shepitko, notableWork, Wings]
-
A.
Wings
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 track from the Black Eyed Peas' concept album *Masters of the Sun Vol. 1*, blending hip hop with socially conscious themes.
-
D.
Wings
Wings is the nickname and commonly used short name for the Dallas Wings, a professional women's basketball team in the WNBA.
-
E.
Wings
"Wings" is a folk-rock song by the Stone Poneys, best known for featuring Linda Ronstadt’s early vocals and helping launch her career.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Wings Triple: [Larisa Shepitko, notableWork, Wings]
Generated description
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.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wings Target entity description: 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.
-
A.
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.
-
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 folk-rock song by the Stone Poneys, best known for featuring Linda Ronstadt’s early vocals and helping launch her career.
-
D.
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.
-
E.
Wings
Wings is the nickname and commonly used short name for the Dallas Wings, a professional women's basketball team in the WNBA.
- F. None of above. chosen
Provenance (5 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_69ca834f70e88190b2d74828b7767ec1 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cdce4bb3408190ac5dae4718ef7cad |
completed | April 2, 2026, 2:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2817858008190b150417f9ef59b48 |
completed | April 5, 2026, 3:36 p.m. |
| NEDg | Description generation | batch_69d2840bb2e881908a7e7a40229769e0 |
completed | April 5, 2026, 3:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d2847c9bb881908a6330dfe2c2c1a4 |
completed | April 5, 2026, 3:49 p.m. |
Created at: March 30, 2026, 8:55 p.m.