Triple
T9264383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Odradek scanner |
E222658
|
entity |
| Predicate | feedbackType |
P87864
|
FINISHED |
| Object | visual feedback |
—
|
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: visual feedback | Statement: [Odradek scanner, feedbackType, visual feedback]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: feedbackType Context triple: [Odradek scanner, feedbackType, visual feedback]
-
A.
issueType
Indicates the specific category or classification assigned to an issue within a tracking or management context.
-
B.
reviewType
Indicates the specific category or kind of review associated with an item, action, or relationship.
-
C.
submissionType
Indicates the specific category or format under which something is submitted (e.g., as a document, assignment, application, or other submission class).
-
D.
support
Indicates that one entity provides assistance, endorsement, or backing to another entity or its actions.
-
E.
featuresReaction
Indicates that one entity exhibits, displays, or includes a particular reaction associated with another entity or context.
- F. None of above. chosen
Provenance (4 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_69ca841f2e808190a64f4c31903a1332 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd0748a1f481909d9d876692cefccc |
completed | April 1, 2026, 11:53 a.m. |
| PD | Predicate disambiguation | batch_69cc7a537bbc8190baee71f556e52a7b |
completed | April 1, 2026, 1:52 a.m. |
| PDg | Predicate description generation | batch_69cc95597be081908ece2491dd2f0f74 |
completed | April 1, 2026, 3:47 a.m. |
Created at: March 30, 2026, 7:32 p.m.