Triple
T20081947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ngorongoro Crater |
E500022
|
entity |
| Predicate | hasShortRains |
P96622
|
FINISHED |
| Object | November to December |
—
|
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: November to December | Statement: [Ngorongoro Crater, hasShortRains, November to December]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasShortRains Context triple: [Ngorongoro Crater, hasShortRains, November to December]
-
A.
hasHighPrecipitation
Indicates that a location or time period experiences a large amount of precipitation, such as rain or snow, relative to a defined standard or average.
-
B.
hasShort
chosen
Indicates that an entity possesses or is characterized by something of short length or duration.
-
C.
hasDrySeasonCause
Indicates that one factor or condition is the underlying cause of a location or region experiencing a dry season.
-
D.
shortSeason
Indicates that the time period or season associated with an entity is relatively brief in duration.
-
E.
hasPrecipitationCriterion
Indicates that something is subject to, defined by, or must satisfy a specified condition related to precipitation (such as amount, type, or occurrence of rainfall, snow, etc.).
- 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_69da627770948190997f486f9a2e370f |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e665588a9c8190886b693b13a215a8 |
completed | April 20, 2026, 5:41 p.m. |
| PD | Predicate disambiguation | batch_69e54cf369b88190931532420517dac7 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:41 p.m.