Triple
T9355850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salt Lake 2002 mascots set |
E225135
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Snowflake
Snowflake is one of the official mascots of the 2002 Winter Olympics in Salt Lake City, representing winter and the Olympic spirit.
|
E793429
|
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: Snowflake | Statement: [Salt Lake 2002 mascots set, hasPart, Snowflake]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Snowflake Context triple: [Salt Lake 2002 mascots set, hasPart, Snowflake]
-
A.
Snowflake
Snowflake is a cloud-based data warehousing platform known for its scalable, high-performance analytics and separation of storage and compute.
-
B.
Snowflake
Snowflake is a censorship-circumvention system that helps users access the Tor network by routing their traffic through volunteer-run proxy nodes embedded in ordinary web browsers.
-
C.
Snowbird
Snowbird is a major ski and snowboard resort in Utah known for its steep terrain, deep powder, and long winter season.
-
D.
Snowfall
Snowfall is an American crime drama television series that explores the early days of the crack cocaine epidemic in 1980s Los Angeles.
-
E.
Snow Wonder
Snow Wonder is a 2005 made-for-television holiday drama film that intertwines multiple characters' lives during a Christmas Eve snowstorm.
- 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: Snowflake Triple: [Salt Lake 2002 mascots set, hasPart, Snowflake]
Generated description
Snowflake is one of the official mascots of the 2002 Winter Olympics in Salt Lake City, representing winter and the Olympic spirit.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Snowflake Target entity description: Snowflake is one of the official mascots of the 2002 Winter Olympics in Salt Lake City, representing winter and the Olympic spirit.
-
A.
Snowflake
Snowflake is a cloud-based data warehousing platform known for its scalable, high-performance analytics and separation of storage and compute.
-
B.
Snowflake
Snowflake is a censorship-circumvention system that helps users access the Tor network by routing their traffic through volunteer-run proxy nodes embedded in ordinary web browsers.
-
C.
Snowbird
Snowbird is a major ski and snowboard resort in Utah known for its steep terrain, deep powder, and long winter season.
-
D.
Snowfall
Snowfall is an American crime drama television series that explores the early days of the crack cocaine epidemic in 1980s Los Angeles.
-
E.
Snow Wonder
Snow Wonder is a 2005 made-for-television holiday drama film that intertwines multiple characters' lives during a Christmas Eve snowstorm.
- 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_69ca842abfd48190949d71c3b86eeba8 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd4f99205c8190a5ad95926ef25497 |
completed | April 1, 2026, 5:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0e45b752c8190b7dd8981ba5be433 |
completed | April 4, 2026, 10:13 a.m. |
| NEDg | Description generation | batch_69d0e5760c0c8190b01a36772cea3058 |
completed | April 4, 2026, 10:18 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d0e616d350819086465c7e491b6e62 |
completed | April 4, 2026, 10:21 a.m. |
Created at: March 30, 2026, 7:42 p.m.