Triple
T1325610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tutu |
E28319
|
entity |
| Predicate | hasClimateRegion |
P285
|
FINISHED |
| Object | tropical climate zone |
—
|
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: tropical climate zone | Statement: [Tutu, hasClimateRegion, tropical climate zone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasClimateRegion Context triple: [Tutu, hasClimateRegion, tropical climate zone]
-
A.
hasClimate
Indicates that an entity possesses or is characterized by a particular type of climate or climatic conditions.
-
B.
hasClimateSystem
Indicates that one entity possesses or is characterized by a particular climate system.
-
C.
hasClimateInfluence
Indicates that one entity affects or contributes to the climate characteristics or climate-related conditions of another entity.
-
D.
hasExtremeWeatherCharacteristic
Indicates that something possesses a notable or defining feature related to extreme weather conditions.
-
E.
hasRegion
chosen
Indicates that an entity includes, contains, or is associated with a specific geographic or administrative region as part of its scope or structure.
- 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_69a498540a2481909e807a762280d3ba |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c19fd2648190932a85eacb3e7ec4 |
completed | March 1, 2026, 10:45 p.m. |
| PD | Predicate disambiguation | batch_69a4beedb49c8190beb5b85cdda05013 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:55 p.m.