Triple
T19833389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Second Kok cabinet |
E476520
|
entity |
| Predicate | unemploymentTrend |
P7393
|
FINISHED |
| Object | declining unemployment |
—
|
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: declining unemployment | Statement: [Second Kok cabinet, unemploymentTrend, declining unemployment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: unemploymentTrend Context triple: [Second Kok cabinet, unemploymentTrend, declining unemployment]
-
A.
economicTrend
chosen
Indicates the general direction or pattern of economic activity or conditions over a period of time.
-
B.
unemploymentPeak
Indicates that the level of unemployment has reached its highest point within a specified time period or context.
-
C.
viewOnUnemployment
Indicates a stance, opinion, or perspective that an entity holds regarding unemployment.
-
D.
latePeriodUnemploymentRateApprox
Indicates the approximate unemployment rate during a later specified time period.
-
E.
laborMarket
Indicates the relationship between workers seeking jobs and employers offering positions, including how wages, employment levels, and working conditions are determined through their interaction.
- 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_69d8e51c7c188190b926f3a2a7b5f881 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e656d0347c8190b586c7fe01b61e97 |
completed | April 20, 2026, 4:39 p.m. |
| PD | Predicate disambiguation | batch_69e5305bda388190a23b7191768107b1 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:50 p.m.