Triple
T25397121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tamralipta Mahavidyalaya |
E636321
|
entity |
| Predicate | hasRegionOfStudents |
P88189
|
FINISHED |
| Object | Purba Medinipur district |
—
|
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: Purba Medinipur district | Statement: [Tamralipta Mahavidyalaya, hasRegionOfStudents, Purba Medinipur district]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegionOfStudents Context triple: [Tamralipta Mahavidyalaya, hasRegionOfStudents, Purba Medinipur district]
-
A.
hasRegionalSchool
Indicates that an entity has an associated school that serves or operates within a specific geographic region.
-
B.
hasStudents
Indicates that an entity (such as a class, school, or teacher) is associated with one or more students.
-
C.
admitsStudentsFrom
chosen
Indicates that an educational institution accepts or enrolls students who come from a specified source, such as a school, region, or program.
-
D.
usesStudentsFor
Indicates that one entity employs or exploits students as a resource or means to carry out its activities or achieve its objectives.
-
E.
studiedInRegion
Indicates that an entity pursued studies or received education within a specified geographic region.
- 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_69e75db263888190b77fff9e2827b9a2 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f7979a073881909a4fde2558e6b6f3 |
completed | May 3, 2026, 6:44 p.m. |
| PD | Predicate disambiguation | batch_69f7961550f88190b7bb8a9155458b54 |
completed | May 3, 2026, 6:38 p.m. |
Created at: April 21, 2026, 1:50 p.m.