Triple
T825656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Snowflake |
E17845
|
entity |
| Predicate | competitor |
P1375
|
FINISHED |
| Object | Amazon Redshift |
E17671
|
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: Amazon Redshift | Statement: [Snowflake, competitor, Amazon Redshift]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amazon Redshift Context triple: [Snowflake, competitor, Amazon Redshift]
-
A.
Amazon Redshift
chosen
Amazon Redshift is a fully managed, cloud-based data warehousing service from Amazon Web Services designed for fast querying and analysis of large datasets using SQL.
-
B.
Azure Synapse Analytics
Azure Synapse Analytics is a cloud-based analytics service from Microsoft that unifies big data and data warehousing to enable large-scale data integration, exploration, and business intelligence.
-
C.
RDS
RDS is a Canadian French-language sports television network that broadcasts a wide range of professional and amateur sporting events.
-
D.
Google BigQuery
Google BigQuery is a fully managed, serverless cloud data warehouse from Google Cloud designed for fast SQL-based analytics on large-scale datasets.
-
E.
PostgreSQL
PostgreSQL is a powerful open-source relational database management system known for its robustness, extensibility, and strong standards compliance.
- 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_69a4937c9c188190aaa216f6b466f452 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ab976094819086d676404d745750 |
completed | March 1, 2026, 9:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a76d9577f081908aa31b1926e04bb8 |
completed | March 3, 2026, 11:24 p.m. |
Created at: March 1, 2026, 7:38 p.m.