Triple
T29585473
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | belg rainy season (Ethiopia) |
E753707
|
entity |
| Predicate | relativeLengthInYear |
P50260
|
FINISHED |
| Object | shorter rainy season |
—
|
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: shorter rainy season | Statement: [belg rainy season (Ethiopia), relativeLengthInYear, shorter rainy season]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relativeLengthInYear Context triple: [belg rainy season (Ethiopia), relativeLengthInYear, shorter rainy season]
-
A.
durationInYears
Indicates the length of time associated with something, measured in whole or fractional years.
-
B.
approximateTimeInYear
Indicates that one time-related entity represents an estimated or non-exact point or interval within a given year for another entity.
-
C.
relativeLength
chosen
Indicates a comparative relationship between entities based on how long they are relative to one another.
-
D.
relativeLengthInYugaCycle
Indicates the proportion of the total Yuga cycle duration that is occupied by a given Yuga or time segment.
-
E.
yearOfReferenceLength
Indicates the specific year for which a referenced duration or length of time is defined or measured.
- 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_6a017969ff908190a7a1a46b3f5ae362 |
completed | May 11, 2026, 6:38 a.m. |
| PD | Predicate disambiguation | batch_6a017609ff4c8190aba8a1864d39a608 |
completed | May 11, 2026, 6:24 a.m. |
Created at: April 28, 2026, 6:10 p.m.