Triple
T1802846
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monsoon Session |
E39756
|
entity |
| Predicate | relatedSession |
P37
|
FINISHED |
| Object | Budget Session |
—
|
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: Budget Session | Statement: [Monsoon Session, relatedSession, Budget Session]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedSession Context triple: [Monsoon Session, relatedSession, Budget Session]
-
A.
relatedService
Indicates that one service is connected or associated with another service in a relevant or dependent way.
-
B.
relatedTo
chosen
Indicates a general, non-specific relationship or association exists between two entities.
-
C.
relatedRegister
Indicates a relationship where one entity is associated with, linked to, or corresponds to a particular register or record in a system.
-
D.
relatedBlock
Indicates that one block is associated with or connected to another block in some relevant way.
-
E.
associatedCamp
Indicates a relationship where an entity is linked or connected to a particular camp, typically as its relevant or affiliated camp.
- 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_69a88632aa588190ba3978fde0db5bbd |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aba67721788190951beae25e885457 |
completed | March 7, 2026, 4:15 a.m. |
| PD | Predicate disambiguation | batch_69aa61d514c081908197ac1f7c7d7a88 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:32 p.m.