Triple
T14519717
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neglected Tropical Diseases program |
E340619
|
entity |
| Predicate | addressesDiseaseType |
P114564
|
FINISHED |
| Object | infectious diseases |
—
|
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: infectious diseases | Statement: [Neglected Tropical Diseases program, addressesDiseaseType, infectious diseases]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: addressesDiseaseType Context triple: [Neglected Tropical Diseases program, addressesDiseaseType, infectious diseases]
-
A.
diseaseType
Indicates that one entity is classified as a specific type or category of disease in relation to another entity.
-
B.
addressesPathogen
Indicates that an action, intervention, or measure is directed toward counteracting, managing, or mitigating a specific pathogen.
-
C.
modelForDisease
Indicates that one entity serves as an experimental or representative model used to study, simulate, or understand a particular disease in another entity.
-
D.
targetsDiseaseVector
Indicates that an entity is directed at, designed to affect, or intended to control a particular disease-carrying vector organism.
-
E.
humanDisease
Indicates that the subject is a disease that affects humans.
- F. None of above. chosen
Provenance (4 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_69d822d9c0408190b9a2b3643e58bb4d |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69de9a70b15c81908773633e989ef704 |
completed | April 14, 2026, 7:50 p.m. |
| PD | Predicate disambiguation | batch_69de5c518fc08190a6ce4d8be05c4c5d |
completed | April 14, 2026, 3:25 p.m. |
| PDg | Predicate description generation | batch_69de5fb5ac548190932f238e37271741 |
completed | April 14, 2026, 3:39 p.m. |
Created at: April 10, 2026, 1:22 a.m.