Triple
T8210865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tu Youyou |
E191811
|
entity |
| Predicate | hasSavedLives |
P8803
|
FINISHED |
| Object | millions of malaria patients worldwide |
—
|
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: millions of malaria patients worldwide | Statement: [Tu Youyou, hasSavedLives, millions of malaria patients worldwide]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSavedLives Context triple: [Tu Youyou, hasSavedLives, millions of malaria patients worldwide]
-
A.
estimatedNumberOfPeopleSaved
chosen
Indicates the approximate count of individuals whose lives were preserved or harm was averted as a result of a particular action, intervention, or entity.
-
B.
usedMeansToRescue
Indicates that one entity employed a particular method, tool, or means in order to carry out a rescue.
-
C.
hasSurvivors
Indicates that one or more entities continue to exist or remain alive after a particular event, condition, or incident.
-
D.
deathContributedTo
Indicates that one entity played a causal or contributing role in bringing about the death of another entity.
-
E.
isForLife
Indicates that something is intended to last or remain valid for the entire duration of a person’s or entity’s life.
- 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_69ca82c8c054819087fedd9a5436b8a3 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb76dd881c8190adcbeb2f33d3295c |
completed | March 31, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69cb36ad01ac81909609b15f6a6c8581 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:44 p.m.