Triple
T9027835
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | App Clips |
E216090
|
entity |
| Predicate | userExperienceGoal |
P6636
|
FINISHED |
| Object | reduce friction for first-time use of app features |
—
|
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: reduce friction for first-time use of app features | Statement: [App Clips, userExperienceGoal, reduce friction for first-time use of app features]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: userExperienceGoal Context triple: [App Clips, userExperienceGoal, reduce friction for first-time use of app features]
-
A.
goalType
Indicates the specific category or nature of a goal associated with an entity or action.
-
B.
usesObjective
Indicates that an agent employs or applies a particular object, tool, or resource to carry out an action or achieve a goal.
-
C.
goals
chosen
Indicates that an entity has objectives, targets, or desired outcomes it aims to achieve.
-
D.
outcomeFocus
Indicates that the primary emphasis or attention is placed on the results or consequences of an action or process.
-
E.
aimOf
Indicates that one entity serves as the goal, purpose, or intended target of another entity’s action, plan, or existence.
- 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_69ca83a5fa88819088144801b4dd7245 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6a7fcb308190af90d6be8700e498 |
completed | April 1, 2026, 12:44 a.m. |
| PD | Predicate disambiguation | batch_69cc5ee132f08190940749c7c522e4c1 |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:07 p.m.