Triple
T24200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IRE Transactions on Communications Systems |
E479
|
entity |
| Predicate | academicField |
P778
|
FINISHED |
| Object | telecommunications |
—
|
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: telecommunications | Statement: [IRE Transactions on Communications Systems, academicField, telecommunications]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: academicField Context triple: [IRE Transactions on Communications Systems, academicField, telecommunications]
-
A.
academicFocus
chosen
Indicates the primary field of study, discipline, or subject area that an entity concentrates on academically.
-
B.
academicAdvisor
Indicates that one entity serves as the academic advisor, providing formal guidance and oversight on academic matters, to another entity.
-
C.
academicDegree
Indicates that an entity holds or has been awarded a specific academic degree.
-
D.
academicStructure
Indicates a hierarchical or organizational relationship within an academic system, such as how programs, departments, courses, or degrees are structured and related to one another.
-
E.
fieldOfWork
Indicates the professional or academic domain in which an entity is primarily engaged or specializes.
- 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_69a243b4ac2c8190b93c303df797b7b2 |
completed | Feb. 28, 2026, 1:24 a.m. |
| NER | Named-entity recognition | batch_69a246e94ca881908f7a7d2c0b293033 |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a246560af88190961ea00b35cf9388 |
completed | Feb. 28, 2026, 1:35 a.m. |
Created at: Feb. 28, 2026, 1:34 a.m.