Triple

T18015125
Position Surface form Disambiguated ID Type / Status
Subject SQLAlchemy E430980 entity
Predicate supportsDatabase P11254 FINISHED
Object CockroachDB NE NERFINISHED

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: CockroachDB | Statement: [SQLAlchemy, supportsDatabase, CockroachDB]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CockroachDB
Context triple: [SQLAlchemy, supportsDatabase, CockroachDB]
  • A. CockroachDB chosen
    CockroachDB is a distributed SQL database designed for horizontal scalability, strong consistency, and high fault tolerance across multiple nodes and regions.
  • B. ScyllaDB
    ScyllaDB is a high-performance, distributed NoSQL database designed as a drop-in replacement for Apache Cassandra, optimized for low latency and high throughput.
  • C. RethinkDB
    RethinkDB is an open-source, distributed NoSQL database designed for real-time applications by pushing live updates to clients as data changes.
  • D. VoltDB
    VoltDB is a high-performance, in-memory, distributed SQL database designed for real-time analytics and transaction processing at massive scale.
  • E. TiKV
    TiKV is an open-source, distributed transactional key-value database designed for horizontal scalability and strong consistency, often used as the storage layer for cloud-native applications.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b904530081908bf341d842464856 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4b522e84c8190a03f6445df9f5ac8 completed April 19, 2026, 10:57 a.m.
Created at: April 10, 2026, 10:24 a.m.