Triple
T29585507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | belg rainy season (Ethiopia) |
E753707
|
entity |
| Predicate | timeRelationTo |
P4137
|
FINISHED |
| Object | precedes kiremt rainy season (Ethiopia) |
—
|
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: precedes kiremt rainy season (Ethiopia) | Statement: [belg rainy season (Ethiopia), timeRelationTo, precedes kiremt rainy season (Ethiopia)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeRelationTo Context triple: [belg rainy season (Ethiopia), timeRelationTo, precedes kiremt rainy season (Ethiopia)]
-
A.
temporalRelation
chosen
Indicates a relationship that specifies how two events or states are positioned relative to each other in time (e.g., before, after, or overlapping).
-
B.
termRelationTo
Indicates a general relational association between one term and another, without specifying the exact nature of that relationship.
-
C.
occursInRelationTo
Indicates that an event, process, or state takes place in the context of, or with reference to, another specified entity or relationship.
-
D.
meetsInRelationTo
Indicates that two or more entities come together or interact within the context of a specified relationship or circumstance.
-
E.
timeCorrelation
Indicates that two events or states are related in time such that changes or occurrences in one are systematically associated with changes or occurrences in the other.
- 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_69f0ef80bf8c8190ad286e99f7df0c63 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69f66d7d3ac48190adef6aa96f5a5b45 |
completed | May 2, 2026, 9:32 p.m. |
| PD | Predicate disambiguation | batch_69f6659d36208190b01412600a4ed57d |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 28, 2026, 6:10 p.m.