Triple

T30387317
Position Surface form Disambiguated ID Type / Status
Subject git.kde.org E772983 entity
Predicate supportedWorkflow P76300 FINISHED
Object code review via Review Board
Code review via Review Board is a web-based peer review process where developers submit patches or changesets for discussion, feedback, and approval before integration into a project’s main codebase.
E1913100 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: code review via Review Board | Statement: [git.kde.org, supportedWorkflow, code review via Review Board]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: code review via Review Board
Triple: [git.kde.org, supportedWorkflow, code review via Review Board]
Generated description
Code review via Review Board is a web-based peer review process where developers submit patches or changesets for discussion, feedback, and approval before integration into a project’s main codebase.

Provenance (5 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_69f2248ef0a48190aa54d4d8ac3e5758 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_6a03809725bc81909c8b61d72d72ca2b completed May 12, 2026, 7:33 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27894dd8d481908e337290363ae57e completed June 9, 2026, 3:32 a.m.
NEDg Description generation batch_6a278a3e743481908898c6b67c87794b completed June 9, 2026, 3:36 a.m.
NED2 Entity disambiguation (via description) batch_6a278abe5bb08190b7d6aad352df1ecd completed June 9, 2026, 3:38 a.m.
Created at: April 29, 2026, 8:01 p.m.