Triple
T4833563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alexander Toshev |
E108001
|
entity |
| Predicate | citationDomain |
P1753
|
FINISHED |
| Object | computer vision literature |
—
|
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: computer vision literature | Statement: [Alexander Toshev, citationDomain, computer vision literature]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: citationDomain Context triple: [Alexander Toshev, citationDomain, computer vision literature]
-
A.
citationType
Indicates the specific kind or category of citation relationship that one entity has to another (e.g., reference, quotation, acknowledgment).
-
B.
citationSystem
Indicates a relationship where one entity specifies or uses a particular system, style, or standard for formatting and managing citations.
-
C.
fieldOfPublication
chosen
Indicates the academic or topical area in which a work is published.
-
D.
citationBy
Indicates that one work is cited or referenced by another work.
-
E.
citationLanguage
Indicates the language in which a cited work or reference is written or presented.
- 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_69bd43fbe444819085cb970706ef73f7 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ff981fc819080d4466c6fe06cf3 |
completed | March 20, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69bd6c21c7f08190846049d31fdfa144 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:25 p.m.