Triple
T7938615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katello |
E184339
|
entity |
| Predicate | usesSearchEngine |
P23048
|
FINISHED |
| Object | Apache Solr |
E358079
|
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: Apache Solr | Statement: [Katello, usesSearchEngine, Apache Solr]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Apache Solr Context triple: [Katello, usesSearchEngine, Apache Solr]
-
A.
Apache Solr
chosen
Apache Solr is an open-source enterprise search platform built on Apache Lucene, widely used for full-text search, faceted navigation, and real-time indexing of large-scale data.
-
B.
Apache Lucene
Apache Lucene is a high-performance, full-featured text search engine library written in Java and widely used as the core indexing and search technology in many applications and search platforms.
-
C.
Jetpack Search
Jetpack Search is a powerful WordPress search enhancement tool that provides fast, relevant, and customizable search results for websites using the Jetpack plugin.
-
D.
Apache Hive
Apache Hive is a data warehouse and SQL-like query system built on top of Hadoop for managing and analyzing large datasets stored in distributed storage.
-
E.
Splunk
Splunk is a data analytics platform that specializes in collecting, indexing, and analyzing machine-generated data for monitoring, security, and operational intelligence.
- 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_69ca8290c21c8190906a5ca6fe2b03c4 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3af0a2048190838d1aeda59fda0b |
completed | March 31, 2026, 3:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5c0e868481908748d340244ea8ea |
completed | March 31, 2026, 5:30 a.m. |
Created at: March 30, 2026, 5:08 p.m.