Triple
T4689787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BCG vaccine |
E104005
|
entity |
| Predicate | effectOnTBTests |
P37225
|
FINISHED |
| Object | can cause false-positive tuberculin skin test |
—
|
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: can cause false-positive tuberculin skin test | Statement: [BCG vaccine, effectOnTBTests, can cause false-positive tuberculin skin test]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectOnTBTests Context triple: [BCG vaccine, effectOnTBTests, can cause false-positive tuberculin skin test]
-
A.
affectsLaboratoryTest
chosen
Indicates that one entity has an influence on, alters, or changes the outcome, value, or interpretation of a laboratory test.
-
B.
effectOnSystem
Indicates the influence, change, or impact that one entity, action, or condition has on the state or behavior of a system.
-
C.
healthEffect
Indicates the impact or consequence that one entity has on the health or well-being of another.
-
D.
areAffectedBy
Indicates that one entity experiences an effect, influence, or impact as a result of another entity or event.
-
E.
effectOnTaxes
Indicates how one entity or action changes, influences, or determines the amount, structure, or treatment of taxes for another entity or situation.
- 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_69bd43df91f481908e9add1b617b60ef |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd66059bfc8190885d26d05dd38df1 |
completed | March 20, 2026, 3:21 p.m. |
| PD | Predicate disambiguation | batch_69bd6219da948190bbbb50f08573ab4d |
completed | March 20, 2026, 3:04 p.m. |
Created at: March 20, 2026, 1:16 p.m.