Triple
T11862157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LM curve |
E282184
|
entity |
| Predicate | shiftsWhen |
P101917
|
FINISHED |
| Object | central bank changes nominal money supply |
—
|
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: central bank changes nominal money supply | Statement: [LM curve, shiftsWhen, central bank changes nominal money supply]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shiftsWhen Context triple: [LM curve, shiftsWhen, central bank changes nominal money supply]
-
A.
hasDynamicShifts
Indicates that something exhibits changes or transitions in state, intensity, or behavior over time rather than remaining constant.
-
B.
marksShiftToward
Indicates a change or transition from one state, condition, or position toward another, highlighting the direction or trend of that shift.
-
C.
hasNumberOfShifts
Indicates the quantity of work shifts associated with a given entity.
-
D.
shiftedUnder
Indicates that one entity has been moved or displaced to a position beneath another entity.
-
E.
hasHistoricalShiftFrom
Indicates a relationship where one state, practice, or condition has been replaced or transformed over time from another earlier state, practice, or condition.
- 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_69d6ab2945d081908a5851c916cbcfb5 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a69b16bc8190999a0c1240f9ce6a |
completed | April 10, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69d8a2573dbc8190ab432e8e28fde6cc |
completed | April 10, 2026, 7:10 a.m. |
| PDg | Predicate description generation | batch_69d8a43cc0c881909fed7cd759fe90b1 |
completed | April 10, 2026, 7:18 a.m. |
Created at: April 8, 2026, 9:43 p.m.