Triple
T5739917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Railway Budget of India |
E126587
|
entity |
| Predicate | post2017Treatment |
P65576
|
FINISHED |
| Object | part of Union Budget of India |
—
|
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: part of Union Budget of India | Statement: [Railway Budget of India, post2017Treatment, part of Union Budget of India]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: post2017Treatment Context triple: [Railway Budget of India, post2017Treatment, part of Union Budget of India]
-
A.
exportTreatment
Indicates the action or process of sending or transferring a treatment (such as a medical, data, or procedural treatment) from one system, location, or context to another for external use or application.
-
B.
treatment
Indicates that one entity is used as a medical or therapeutic intervention to address, manage, or cure a condition affecting another entity.
-
C.
importTreatment
Indicates that one entity brings or transfers a treatment or therapeutic intervention into another context, system, or location for use or application.
-
D.
subsequentTreatment
Indicates that one treatment occurs after and in response to a prior treatment or medical event.
-
E.
treats
Indicates that one entity provides medical care or therapeutic intervention to 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_69c0083179548190b384b0bf3c08ca4d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0255f302c819094f97b4defeded07 |
completed | March 22, 2026, 5:22 p.m. |
| PD | Predicate disambiguation | batch_69c021c8195481909419808b002628aa |
completed | March 22, 2026, 5:07 p.m. |
| PDg | Predicate description generation | batch_69c022a50c048190aff24c63e7039dd6 |
completed | March 22, 2026, 5:11 p.m. |
Created at: March 22, 2026, 3:48 p.m.