Triple

T4555340
Position Surface form Disambiguated ID Type / Status
Subject Laravel E120464 entity
Predicate supports P516 FINISHED
Object Redis E183380 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: Redis | Statement: [Laravel, supports, Redis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Redis
Context triple: [Laravel, supports, Redis]
  • A. Redis chosen
    Redis is an in-memory data structure store commonly used as a database, cache, and message broker known for its high performance and low latency.
  • B. Memcached
    Memcached is a high-performance, distributed in-memory caching system commonly used to speed up dynamic web applications by reducing database load.
  • C. Amazon ElastiCache
    Amazon ElastiCache is a fully managed in-memory data store and caching service that improves application performance by enabling fast, sub-millisecond data retrieval.
  • D. RocksDB
    RocksDB is a high-performance, embeddable key–value store developed by Facebook, optimized for fast storage on flash and solid-state drives using a Log-Structured Merge-Tree (LSM) architecture.
  • E. Apache Cassandra
    Apache Cassandra is a highly scalable, distributed NoSQL database designed for handling large amounts of data across many commodity servers with high availability and no single point of failure.
  • 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_69bd4636f1648190a701445c2fcd9c17 completed March 20, 2026, 1:05 p.m.
NER Named-entity recognition batch_69bd5813af948190b10b02dadf6496bf completed March 20, 2026, 2:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdc57d59f88190857cbda79caf3c38 completed March 20, 2026, 10:09 p.m.
Created at: March 20, 2026, 1:09 p.m.