Triple
T735470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States–Cuba relations |
E14919
|
entity |
| Predicate | ongoingStatus |
P127
|
FINISHED |
| Object | partially normalized but largely adversarial |
—
|
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: partially normalized but largely adversarial | Statement: [United States–Cuba relations, ongoingStatus, partially normalized but largely adversarial]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ongoingStatus Context triple: [United States–Cuba relations, ongoingStatus, partially normalized but largely adversarial]
-
A.
laterStatus
Indicates that one entity represents a subsequent or resulting status or condition of another entity in time.
-
B.
continuityStatus
Indicates the state of whether something continues without interruption or has been broken, paused, or reset over time.
-
C.
status
chosen
Indicates the current condition, state, or standing of an entity within a given context.
-
D.
operatingStatus
Indicates whether an entity is currently functioning, active, or in service versus inactive, closed, or out of service.
-
E.
automationStatus
Indicates whether a process, task, or system is being performed automatically or requires manual intervention.
- 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_69a4934d9930819099eed80096b0597d |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a66820548190b373deb117187c2c |
completed | March 1, 2026, 8:49 p.m. |
| PD | Predicate disambiguation | batch_69a4a4fafee081909bf356854c09aaff |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.