Triple
T29861885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harvey J. Alter |
E758337
|
entity |
| Predicate | helpedReduce |
P9925
|
FINISHED |
| Object | risk of transfusion-associated hepatitis C |
—
|
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: risk of transfusion-associated hepatitis C | Statement: [Harvey J. Alter, helpedReduce, risk of transfusion-associated hepatitis C]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: helpedReduce Context triple: [Harvey J. Alter, helpedReduce, risk of transfusion-associated hepatitis C]
-
A.
reduces
chosen
Indicates that one entity causes a decrease in the amount, intensity, degree, or impact of another entity.
-
B.
helpedCause
Indicates that one entity contributed to bringing about, enabling, or facilitating an outcome or event involving another entity.
-
C.
reduction
Indicates a relationship where something is decreased in amount, size, intensity, or degree compared to a prior state or reference.
-
D.
helpsIn
Indicates that one entity provides assistance, support, or aid to another entity in performing or achieving a particular task, activity, or goal.
-
E.
oftenHelps
Indicates that one entity frequently provides assistance or support to another.
- 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_69f2245b4dec8190b85f664d918a00a5 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f67685c8c0819089a31631bfba0797 |
completed | May 2, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69f673c4abec8190bc2379e66f4af0a9 |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 29, 2026, 5:49 p.m.