Triple
T21958698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taenia |
E542262
|
entity |
| Predicate | higherPrevalenceRegions |
P144895
|
FINISHED |
| Object | areas with poor sanitation |
—
|
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: areas with poor sanitation | Statement: [Taenia, higherPrevalenceRegions, areas with poor sanitation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: higherPrevalenceRegions Context triple: [Taenia, higherPrevalenceRegions, areas with poor sanitation]
-
A.
higherPrevalenceRegion
chosen
Indicates that a condition, characteristic, or phenomenon occurs more frequently in one region compared to another.
-
B.
countryOrRegionOfPrevalence
Indicates the country or geographic region where something (such as a condition, practice, or phenomenon) is most commonly found or occurs most frequently.
-
C.
prevalentIn
Indicates that something occurs frequently or is commonly found within a particular context, group, or environment.
-
D.
populationRegion
Indicates that a specified population is located within or associated with a particular geographic region.
-
E.
primaryRegionOfPopularity
Indicates the geographic region where something is most widely used, favored, or popular compared to other regions.
- 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_69e0c47fab1081908dc74a6545dbb051 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1244204f081909742d4fe138610d6 |
completed | April 28, 2026, 9:18 p.m. |
| PD | Predicate disambiguation | batch_69e6f601f2188190893bcdde0cf58ad6 |
completed | April 21, 2026, 3:58 a.m. |
Created at: April 16, 2026, 8 p.m.