Triple
T38559733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mycobacterium ulcerans |
E928043
|
entity |
| Predicate | highEndemicityRegion |
P55272
|
FINISHED |
| Object | West Africa |
—
|
NE NERFINISHED |
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: West Africa | Statement: [Mycobacterium ulcerans, highEndemicityRegion, West Africa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: highEndemicityRegion Context triple: [Mycobacterium ulcerans, highEndemicityRegion, West Africa]
-
A.
higherPrevalenceRegion
Indicates that a condition, characteristic, or phenomenon occurs more frequently in one region compared to another.
-
B.
isEndemicTo
Indicates that something naturally occurs and is restricted to a particular geographic area or region.
-
C.
countryOrRegionOfPrevalence
chosen
Indicates the country or geographic region where something (such as a condition, practice, or phenomenon) is most commonly found or occurs most frequently.
-
D.
isPopulousRegionOf
Indicates that a region has a large population and is located within or associated with a specified larger area or entity.
-
E.
eligibleRegion
Indicates the geographic area within which something (such as an offer, service, or rule) is valid, applicable, or permitted.
- 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_69f76eb8d1808190a588af29d8b266d6 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fe08d2b2e48190ac7be6d62d4a44a3 |
completed | May 8, 2026, 4:01 p.m. |
| PD | Predicate disambiguation | batch_69fe06cd3af08190ae25de0dc0cdd573 |
completed | May 8, 2026, 3:52 p.m. |
Created at: May 3, 2026, 4:32 p.m.