Triple
T9712663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MATE Settings Daemon |
E235056
|
entity |
| Predicate | stopsWith |
P85453
|
FINISHED |
| Object | user logout |
—
|
LITERAL 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: user logout | Statement: [MATE Settings Daemon, stopsWith, user logout]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stopsWith Context triple: [MATE Settings Daemon, stopsWith, user logout]
-
A.
stopsPattern
Indicates that one entity halts, interrupts, or prevents the continuation of a recurring or structured pattern involving another entity.
-
B.
stoppedAt
Indicates that an entity has come to a halt or pause at a specific location or point in time.
-
C.
hasStop
Indicates that something (such as a route, service, or journey) includes or is associated with a particular stop or stopping point.
-
D.
terminatesOn
chosen
Indicates that one process, event, or state causes or marks the ending of another at a specific time or condition.
-
E.
hasStopType
Indicates that a stop or stopping point is classified as having a particular type or category of stop.
- F. None of above.
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_69ca84cd8fa0819090a5e243ceb37003 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9e0705f8819095852263009c28c5 |
completed | April 1, 2026, 10:36 p.m. |
| PD | Predicate disambiguation | batch_69cd03bfeca08190924fca43aaa9c10f |
completed | April 1, 2026, 11:38 a.m. |
Created at: March 30, 2026, 8:19 p.m.