Triple
T4294603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marcin Zukowski |
E99679
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Snowflake |
E17845
|
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: Snowflake | Statement: [Marcin Zukowski, notableWork, Snowflake]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Snowflake Context triple: [Marcin Zukowski, notableWork, Snowflake]
-
A.
Snowflake
chosen
Snowflake is a cloud-based data warehousing platform known for its scalable, high-performance analytics and separation of storage and compute.
-
B.
Snowbird
Snowbird is a major ski and snowboard resort in Utah known for its steep terrain, deep powder, and long winter season.
-
C.
Snowfall
Snowfall is an American crime drama television series that explores the early days of the crack cocaine epidemic in 1980s Los Angeles.
-
D.
Snowlets
Snowlets are the four snowy owl mascots created to represent the 1998 Winter Olympics in Nagano, Japan.
-
E.
Carbon Glacier
Carbon Glacier is a major valley glacier on the north slope of Mount Rainier in Washington, notable for its great thickness and low terminus elevation.
- 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_69b3455175088190aa79c6e03b86647e |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35083f87c8190a3d3b323e76ab575 |
completed | March 12, 2026, 11:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5c740c4a081909a63fb957f2926ae |
completed | March 14, 2026, 8:38 p.m. |
Created at: March 12, 2026, 11:08 p.m.