Triple
T2488672
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kota |
E55987
|
entity |
| Predicate | hasEducationalFeature |
P40345
|
FINISHED |
| Object | large number of private coaching institutes |
—
|
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: large number of private coaching institutes | Statement: [Kota, hasEducationalFeature, large number of private coaching institutes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEducationalFeature Context triple: [Kota, hasEducationalFeature, large number of private coaching institutes]
-
A.
hasEducationalUse
Indicates that something is intended to be used for educational or instructional purposes.
-
B.
offersEducationMode
Indicates that an entity provides a particular mode or format in which education or instruction is delivered.
-
C.
hasEducationalAudience
Indicates that something is intended for or directed toward a specific educational audience or learner group.
-
D.
hasEducationalBrand
Indicates that one entity possesses, is associated with, or operates under a particular educational brand or branding identity.
-
E.
hasEducationalSupportFrom
Indicates that one entity receives educational assistance, guidance, or resources from another entity.
- 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.