Triple
T30564527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KInfoCenter |
E777934
|
entity |
| Predicate | category |
P87
|
FINISHED |
| Object |
KDE System tools
KDE System tools is a category within the KDE desktop environment that groups together utilities for managing and monitoring system settings, hardware, and performance.
|
E1922556
|
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: KDE System tools | Statement: [KInfoCenter, category, KDE System tools]
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: KDE System tools Triple: [KInfoCenter, category, KDE System tools]
Generated description
KDE System tools is a category within the KDE desktop environment that groups together utilities for managing and monitoring system settings, hardware, and performance.
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_69f2249ed41c8190b175170ecfd6e1c5 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6890d8cc0819080615205c4bc9b60 |
completed | May 2, 2026, 11:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a2856f8af9c8190aabb7c57dea3b121 |
completed | June 9, 2026, 6:10 p.m. |
| NEDg | Description generation | batch_6a285a4e706c81909bc1e0aef5f5c040 |
completed | June 9, 2026, 6:24 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a285b8ba9908190a18bdc26198d0f4a |
completed | June 9, 2026, 6:29 p.m. |
Created at: April 29, 2026, 8:21 p.m.