Triple
T1507460
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U21 |
E33932
|
entity |
| Predicate | hasAreaOfWork |
P3
|
FINISHED |
| Object | student mobility |
—
|
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: student mobility | Statement: [U21, hasAreaOfWork, student mobility]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAreaOfWork Context triple: [U21, hasAreaOfWork, student mobility]
-
A.
fieldOfWork
chosen
Indicates the professional or academic domain in which an entity is primarily engaged or specializes.
-
B.
hasResearchArea
Indicates that an entity (such as a person, project, or organization) is associated with or focused on a particular field or area of research.
-
C.
competenceArea
Indicates that one entity has a particular domain, field, or area in which it possesses competence, expertise, or responsibility.
-
D.
notableWorkArea
Indicates the field or domain in which an entity’s significant work or contributions are primarily focused.
-
E.
worksWith
Indicates that two entities collaborate or perform tasks together in a shared work-related context.
- 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_69a885f352a4819099b24ff15489dede |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90584b8b881908e112c7e59163812 |
completed | March 5, 2026, 4:24 a.m. |
| PD | Predicate disambiguation | batch_69a88727ce48819089b482cdc25453d1 |
completed | March 4, 2026, 7:25 p.m. |
Created at: March 4, 2026, 7:24 p.m.