Triple
T22701043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Common Law Admission Test |
E561321
|
entity |
| Predicate | applicablePrograms |
P149376
|
FINISHED |
| Object | BA LL.B (Hons) |
—
|
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: BA LL.B (Hons) | Statement: [Common Law Admission Test, applicablePrograms, BA LL.B (Hons)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: applicablePrograms Context triple: [Common Law Admission Test, applicablePrograms, BA LL.B (Hons)]
-
A.
sponsoredPrograms
Indicates that an entity provides financial or resource support to specific programs or initiatives.
-
B.
offersProgramsThrough
Indicates that one entity provides or delivers its programs, services, or courses by means of, or via the infrastructure or platform of, another entity.
-
C.
appliesProgram
Indicates that an agent initiates or carries out a specific program, procedure, or course of action on or for a target entity.
-
D.
recommendedProgram
Indicates that one entity suggests or endorses another entity as a suitable or preferred program for a particular purpose or user.
-
E.
agencyProgramme
Indicates that an agency is responsible for, manages, or is associated with a particular programme.
- 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_69e2454e615481909c177440be559d2c |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f178ca683c81909f6b4e26b85c99c1 |
completed | April 29, 2026, 3:19 a.m. |
| PD | Predicate disambiguation | batch_69ee62bd657c81909f7b01245b080a5f |
completed | April 26, 2026, 7:08 p.m. |
| PDg | Predicate description generation | batch_69ee8843d3308190b6e22bb98ae5c3d8 |
completed | April 26, 2026, 9:48 p.m. |
Created at: April 17, 2026, 3:15 p.m.