Triple
T735390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States–Cuba relations |
E14919
|
entity |
| Predicate | began |
P19545
|
FINISHED |
| Object | 19th century |
—
|
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: 19th century | Statement: [United States–Cuba relations, began, 19th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: began Context triple: [United States–Cuba relations, began, 19th century]
-
A.
beganWith
Indicates that one event, process, or state started with or was initiated by another specified event, process, or state.
-
B.
became
Indicates a change of state or status in which one entity transitions into or assumes the role, condition, or identity of another.
-
C.
beganInYear
Indicates that an event, process, or state started in a specific calendar year.
-
D.
occupationBegan
Indicates the point in time when an entity started holding a particular occupation or job.
-
E.
developmentBegan
Indicates that the process of creating or developing something was initiated at a particular time or under certain conditions.
- 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_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. |
| PDg | Predicate description generation | batch_69a4a66658948190bdae6e521951954f |
completed | March 1, 2026, 8:49 p.m. |
Created at: March 1, 2026, 7:37 p.m.