Triple
T16368460
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kabwe |
E397497
|
entity |
| Predicate | hazardRanking |
P60801
|
FINISHED |
| Object | listed among world’s most polluted places by some environmental groups |
—
|
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: listed among world’s most polluted places by some environmental groups | Statement: [Kabwe, hazardRanking, listed among world’s most polluted places by some environmental groups]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hazardRanking Context triple: [Kabwe, hazardRanking, listed among world’s most polluted places by some environmental groups]
-
A.
geologicHazardLevel
Indicates the degree of potential danger or risk posed by geologic processes or conditions at a given location.
-
B.
hazardScope
Indicates the range or extent within which a particular hazard is relevant, applicable, or has effect.
-
C.
hazardType
Indicates the specific kind or category of hazard associated with an entity or situation.
-
D.
hasHazardLevel
chosen
Indicates that an entity is associated with a specified degree or category of risk or danger.
-
E.
floodRiskCategory
Indicates the level or classification of flood risk associated with an entity, such as a location or asset.
- 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_69d87f2778dc8190aa95c7572db127e6 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2ff3f0694819097faa1c1447a9e97 |
completed | April 18, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69e226f37ecc819082af58b29b4e39d1 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:08 a.m.