Triple
T26514465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | विद्या भारती |
E669773
|
entity |
| Predicate | संबंधित_क्षेत्र |
P6979
|
FINISHED |
| Object | स्कूल शिक्षा |
—
|
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: स्कूल शिक्षा | Statement: [विद्या भारती, संबंधित_क्षेत्र, स्कूल शिक्षा]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: संबंधित_क्षेत्र Context triple: [विद्या भारती, संबंधित_क्षेत्र, स्कूल शिक्षा]
-
A.
relatedField
chosen
Indicates that one field, topic, or area of study is connected or relevant to another in subject matter or application.
-
B.
relatedPass
Indicates that one pass is associated with or connected to another pass in some relevant way.
-
C.
relatedWorkField
Indicates that one work is associated with or pertains to the same or a relevant field, discipline, or area of activity as another work.
-
D.
relatedDialectArea
Indicates that one dialect area is geographically, historically, or linguistically connected to another dialect area.
-
E.
relatedTo
Indicates a general, non-specific relationship or association exists between two entities.
- 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_69eeb31b6dcc8190b30632dc3928a0c0 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f62d53ad58819080c5227c7a729d15 |
completed | May 2, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69f62c15952881908a5ea0c25904afec |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 27, 2026, 1:22 a.m.