Triple
T27170833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VisiCorp |
E682903
|
entity |
| Predicate | softwareCategoryFocus |
P162628
|
FINISHED |
| Object | office productivity |
—
|
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: office productivity | Statement: [VisiCorp, softwareCategoryFocus, office productivity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: softwareCategoryFocus Context triple: [VisiCorp, softwareCategoryFocus, office productivity]
-
A.
softwareCategoryOfMainProduct
Indicates that a software item serves as the primary or main product within a specified software category.
-
B.
softwareFor
Indicates that one entity is designed, intended, or used to operate on, support, or be compatible with another entity as software.
-
C.
softwareName
Indicates that one entity is the name or title of a software application associated with another entity.
-
D.
targetedSoftware
Indicates that a particular piece of software is the specific focus or target of an action, operation, or effect.
-
E.
developmentCategory
Indicates the classification of an entity according to a particular stage, type, or area of development.
- 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_69eefacf6e788190a75a64399d9e3109 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f62d89b89c8190afb372a8172111e7 |
completed | May 2, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69f62c1762f881908c25e8f70ecd5041 |
completed | May 2, 2026, 4:53 p.m. |
| PDg | Predicate description generation | batch_69f62cd1912c8190ab3f3288442115a4 |
completed | May 2, 2026, 4:56 p.m. |
Created at: April 27, 2026, 9:23 a.m.