Triple
T27709107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BLDTF |
E698628
|
entity |
| Predicate | coveredDiseaseCommonName |
P153793
|
FINISHED |
| Object | black lung disease |
—
|
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: black lung disease | Statement: [BLDTF, coveredDiseaseCommonName, black lung disease]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coveredDiseaseCommonName Context triple: [BLDTF, coveredDiseaseCommonName, black lung disease]
-
A.
diseaseName
chosen
Indicates that the associated value specifies the name or designation of a particular disease.
-
B.
diseaseType
Indicates that one entity is classified as a specific type or category of disease in relation to another entity.
-
C.
commonlyIdentifiedWith
Indicates that two entities are widely regarded or treated as the same or equivalent, even if they are formally distinct.
-
D.
causesDiseaseType
Indicates that one entity is responsible for causing a specific type or category of disease in another entity.
-
E.
diseaseUsed
Indicates that a particular disease is employed or utilized as a tool, model, or condition within a given context or process.
- 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_69ef590f655c81909f93893b3b3219b2 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f6afebd7ec8190ab696f363d84abf0 |
completed | May 3, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69f6aca204148190850a3dc325bc07b7 |
completed | May 3, 2026, 2:02 a.m. |
Created at: April 27, 2026, 3:01 p.m.