Triple
T7569918
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monetary policy of India |
E179212
|
entity |
| Predicate | MPCMeetingFrequency |
P2557
|
FINISHED |
| Object | at least four times a year |
—
|
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: at least four times a year | Statement: [Monetary policy of India, MPCMeetingFrequency, at least four times a year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: MPCMeetingFrequency Context triple: [Monetary policy of India, MPCMeetingFrequency, at least four times a year]
-
A.
meetingFrequency
chosen
Indicates how often a meeting or recurring gathering takes place over a given period.
-
B.
typicalMeetingMonth
Indicates the month in which an entity most commonly or usually holds its meetings.
-
C.
serviceFrequencyType
Indicates how often a service occurs or is scheduled within a given time period.
-
D.
meetsRegularly
Indicates that two or more entities come together on a recurring or scheduled basis.
-
E.
typicalNumberOfMeetingsPerSeason
Indicates the usual or average count of meetings that occur within a single season.
- 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_69c69f316e50819081a271c85c06f918 |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c6f91ec780819099de6227a27bf5a5 |
completed | March 27, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69c6f4de77048190b8769e717fdcf8e7 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:51 p.m.