Triple
T36114640
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guardian system |
E1044587
|
entity |
| Predicate | visualFeedbackType |
P11599
|
FINISHED |
| Object | grid-like boundary lines |
—
|
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: grid-like boundary lines | Statement: [Guardian system, visualFeedbackType, grid-like boundary lines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: visualFeedbackType Context triple: [Guardian system, visualFeedbackType, grid-like boundary lines]
-
A.
visualField
Indicates the spatial region in which a visual system or observer can detect and perceive visual stimuli.
-
B.
visualForm
chosen
Indicates the visual appearance, shape, or structural pattern that characterizes how something looks.
-
C.
visualCompanion
Indicates that one entity serves as a visual counterpart, partner, or accompanying element to another in a visual context.
-
D.
visualElements
Indicates that one entity contains, uses, or is characterized by specific visual components or graphical features associated with another entity.
-
E.
visualExperience
Indicates a relationship where an entity undergoes or has a particular experience involving visual perception or seeing.
- 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_69f76e344a4c8190af3858c6d78ba88f |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b3e2f3c08190be4fd1ae4fa1266d |
completed | May 3, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69f7b1bcc47081909fe7d592ac69006c |
completed | May 3, 2026, 8:36 p.m. |
Created at: May 3, 2026, 4:08 p.m.