Triple
T3576339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | International Monetary and Financial Committee |
E75697
|
entity |
| Predicate | typicalMeetingTime |
P6833
|
FINISHED |
| Object | during IMF–World Bank Spring Meetings |
—
|
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: during IMF–World Bank Spring Meetings | Statement: [International Monetary and Financial Committee, typicalMeetingTime, during IMF–World Bank Spring Meetings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalMeetingTime Context triple: [International Monetary and Financial Committee, typicalMeetingTime, during IMF–World Bank Spring Meetings]
-
A.
meetingDay
Indicates the specific day on which a meeting is scheduled or takes place between the related entities.
-
B.
typicalTimes
chosen
Indicates the usual or characteristic times at which an event, activity, or condition typically occurs.
-
C.
typicalAppointment
Indicates that an appointment represents a standard, usual, or commonly occurring scheduling arrangement between entities.
-
D.
typicalSchedule
Indicates the usual or standard timing and sequence of activities or events associated with an entity.
-
E.
typicalMeetingMonth
Indicates the month in which an entity most commonly or usually holds its meetings.
- 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_69ad85d5e3008190bdfe0bacdd1f5a1b |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc0dba238819083a1d09005c312b8 |
completed | March 8, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69adb83810c481909c645c08b978edc1 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:21 p.m.