Triple
T8248380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hydra |
E192900
|
entity |
| Predicate | supportsProtocol |
P203
|
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: [Hydra, supportsProtocol, Redis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Redis Context triple: [Hydra, supportsProtocol, 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.
RethinkDB
RethinkDB is an open-source, distributed NoSQL database designed for real-time applications by pushing live updates to clients as data changes.
-
D.
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.
-
E.
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.
- 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_69ca82de7b8c81908d8106f8a53cff9b |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb78c6b3c48190a3ecebf449766124 |
completed | March 31, 2026, 7:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd3530ca148190a28761622d0cf663 |
completed | April 1, 2026, 3:09 p.m. |
Created at: March 30, 2026, 5:48 p.m.