Triple
T9327456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | White Christmas (1954 film) |
E224426
|
entity |
| Predicate | featuresSong |
P2152
|
FINISHED |
| Object |
Snow
"Snow" is a festive song from the 1954 musical film *White Christmas*, celebrated for its nostalgic lyrics about the beauty and romance of wintertime snowfall.
|
E792209
|
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: Snow | Statement: [White Christmas (1954 film), featuresSong, Snow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Snow Context triple: [White Christmas (1954 film), featuresSong, Snow]
-
A.
Snow
"Snow" is a political and philosophical novel by Turkish Nobel laureate Orhan Pamuk that explores identity, secularism, and Islamism in contemporary Turkey.
-
B.
Snow
Snow is a white color variant of the iMac G3, known for its clean, minimalist appearance among the line’s iconic translucent and colorful designs.
-
C.
Snow
"Snow" is a concept progressive rock double album by Spock’s Beard, known for its elaborate storytelling and complex musicianship.
-
D.
Snow
"Snow" is a notable abstract painting by British artist Howard Hodgkin, recognized for its expressive brushwork and evocative use of color to suggest memory and atmosphere.
-
E.
Snow
Snow is a common English surname borne by various notable figures in literature, science, and public life.
- 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: Snow Triple: [White Christmas (1954 film), featuresSong, Snow]
Generated description
"Snow" is a festive song from the 1954 musical film *White Christmas*, celebrated for its nostalgic lyrics about the beauty and romance of wintertime snowfall.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Snow Target entity description: "Snow" is a festive song from the 1954 musical film *White Christmas*, celebrated for its nostalgic lyrics about the beauty and romance of wintertime snowfall.
-
A.
Snow
"Snow" is a song featured on the album *Back to Scratch* by Welsh singer-songwriter Charlotte Church.
-
B.
Snow
"Snow" is a notable abstract painting by British artist Howard Hodgkin, recognized for its expressive brushwork and evocative use of color to suggest memory and atmosphere.
-
C.
Snow
"Snow" is a concept progressive rock double album by Spock’s Beard, known for its elaborate storytelling and complex musicianship.
-
D.
Snow
"Snow" is a political and philosophical novel by Turkish Nobel laureate Orhan Pamuk that explores identity, secularism, and Islamism in contemporary Turkey.
-
E.
Snow
Snow is a common English surname borne by various notable figures in literature, science, and public life.
- 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_69ca8427a0c08190b749831d5ea98f02 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd37aa78648190b786b50402b15569 |
completed | April 1, 2026, 3:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0c7e940d481909882dd920f0c6c1d |
completed | April 4, 2026, 8:12 a.m. |
| NEDg | Description generation | batch_69d0c976a0308190ba66990fe0a3f33e |
completed | April 4, 2026, 8:19 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d0ce28aaf48190a1e6b4040353c6b9 |
completed | April 4, 2026, 8:39 a.m. |
Created at: March 30, 2026, 7:39 p.m.