Triple
T2488679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kota |
E55987
|
entity |
| Predicate | educationalImportance |
P40346
|
FINISHED |
| Object | national center for entrance exam preparation |
—
|
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: national center for entrance exam preparation | Statement: [Kota, educationalImportance, national center for entrance exam preparation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: educationalImportance Context triple: [Kota, educationalImportance, national center for entrance exam preparation]
-
A.
educationalImpact
Indicates the effect or influence that one entity has on the learning, knowledge, or educational outcomes of another.
-
B.
educationalFocus
Indicates the primary subject area or theme that an educational activity, program, or resource is centered on.
-
C.
educates
Indicates that one entity provides instruction, knowledge, or training to another entity.
-
D.
educationRight
Indicates that an entity holds a right or entitlement to receive education or educational opportunities.
-
E.
educationalApproach
Indicates the method, strategy, or philosophy used to guide teaching and learning within an educational context.
- 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_69ab49e670a88190b928e08302381710 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd20b6d008190acec0eb172e218c9 |
completed | March 7, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69abd0b7cf088190bcff4dac6150044c |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd209d934819093600889af9104c3 |
completed | March 7, 2026, 7:21 a.m. |
Created at: March 6, 2026, 9:45 p.m.