Triple
T7847577
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BLBA |
E181959
|
entity |
| Predicate | targetsRisk |
P62537
|
FINISHED |
| Object | respiratory disease from coal dust exposure |
—
|
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: respiratory disease from coal dust exposure | Statement: [BLBA, targetsRisk, respiratory disease from coal dust exposure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetsRisk Context triple: [BLBA, targetsRisk, respiratory disease from coal dust exposure]
-
A.
riskType
Indicates the category or nature of risk associated with an entity, event, or relationship.
-
B.
riskElement
chosen
Indicates that one entity is a risk-related component, factor, or contributor associated with another entity within a risk context.
-
C.
riskBasis
Indicates the underlying factor, condition, or rationale that forms the basis for assessing or assigning risk in a given context.
-
D.
riskGroup
Indicates that an entity belongs to a category of individuals or items that share an elevated level of risk relative to others.
-
E.
riskAddressed
Indicates that a particular risk has been identified and is being mitigated, managed, or otherwise handled by an associated action, control, or measure.
- 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_69ca8285d6488190a95d4c02d7354b53 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb164105fc8190a60aaa27dd619d5a |
completed | March 31, 2026, 12:33 a.m. |
| PD | Predicate disambiguation | batch_69cae92180f88190ae3d44c3de7adc93 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:49 p.m.