Triple
T320692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Korean won |
E6407
|
entity |
| Predicate | crisisPeriod |
P302
|
FINISHED |
| Object | late 1990s |
—
|
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: late 1990s | Statement: [South Korean won, crisisPeriod, late 1990s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crisisPeriod Context triple: [South Korean won, crisisPeriod, late 1990s]
-
A.
historicalPeriodOfGreatestDanger
Indicates the time period in which an entity faced its highest level of risk, threat, or vulnerability.
-
B.
focusPeriod
Indicates the specific time span during which attention, activity, or analysis is concentrated on something.
-
C.
timePeriod
chosen
Indicates the specific span or interval of time during which an event, state, or relationship occurs or is valid.
-
D.
occurredDuring
Indicates that one event or action took place within the temporal span of another event or time period.
-
E.
collapsedDuring
Indicates that one entity structurally failed or fell down while another specified event or process was occurring.
- 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_69a2e7933d6c8190bb2592ad13286ef2 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea8047c08190872c875e00f6e7dd |
completed | Feb. 28, 2026, 1:15 p.m. |
| PD | Predicate disambiguation | batch_69a2e946607081909c8b97473aaf8d1b |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.