Triple
T5816857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PS |
E129006
|
entity |
| Predicate | examAudience |
P62009
|
FINISHED |
| Object | surveying graduates |
—
|
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: surveying graduates | Statement: [PS, examAudience, surveying graduates]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: examAudience Context triple: [PS, examAudience, surveying graduates]
-
A.
typicalAudience
Indicates the group of people for whom something (such as a work, product, or resource) is primarily intended or most suitable.
-
B.
examType
Indicates the specific category or format of an exam associated with an assessment or testing event.
-
C.
examProvider
Indicates that one entity is the organization or individual responsible for creating, administering, or supplying an exam to another entity.
-
D.
relatesToAudience
chosen
Indicates a general relationship or relevance between something and a particular audience or group of recipients.
-
E.
academicAudience
Indicates that something is intended for, directed toward, or primarily relevant to an academic or scholarly audience.
- 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_69c0084869e881908d7859492183ca7b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0400f1af881908d376ea4793f6dea |
completed | March 22, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_69c0333fdd7081908d829265caa2ac11 |
completed | March 22, 2026, 6:21 p.m. |
Created at: March 22, 2026, 3:53 p.m.