Triple
T25909987
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Delhi University LL.M. Entrance Test |
E652864
|
entity |
| Predicate | targetProgramme |
P6928
|
FINISHED |
| Object | LL.M. (Master of Laws) |
—
|
NE NERFINISHED |
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: LL.M. (Master of Laws) | Statement: [Delhi University LL.M. Entrance Test, targetProgramme, LL.M. (Master of Laws)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetProgramme Context triple: [Delhi University LL.M. Entrance Test, targetProgramme, LL.M. (Master of Laws)]
-
A.
agencyProgramme
Indicates that an agency is responsible for, manages, or is associated with a particular programme.
-
B.
hasProgramme
chosen
Indicates that an entity is associated with or offers a particular programme (such as a course of study, plan, or structured set of activities).
-
C.
targetAudienceOfPrograms
Indicates that a particular group or entity is the intended audience or recipient of certain programs.
-
D.
programmeName
Indicates that an entity has or is identified by a specific programme’s name.
-
E.
intendedProgram
Indicates the academic or training program that an entity plans or expects to pursue, rather than one they are currently enrolled in or have completed.
- 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_69e7ab3d3f8481909bc53ed64c06af33 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f66c5c13808190887180099745673b |
completed | May 2, 2026, 9:27 p.m. |
| PD | Predicate disambiguation | batch_69f66abddc448190a488852f8abdeb2c |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 22, 2026, 8:28 a.m.