Triple
T875369
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Advance Market Commitment for pneumococcal vaccines |
E18906
|
entity |
| Predicate | hasTargetPathogen |
P14889
|
FINISHED |
| Object | Streptococcus pneumoniae |
—
|
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: Streptococcus pneumoniae | Statement: [Advance Market Commitment for pneumococcal vaccines, hasTargetPathogen, Streptococcus pneumoniae]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTargetPathogen Context triple: [Advance Market Commitment for pneumococcal vaccines, hasTargetPathogen, Streptococcus pneumoniae]
-
A.
pathogenType
Indicates the specific kind or category of pathogen associated with or responsible for an entity or condition.
-
B.
pathogenGenus
Indicates that one entity is a pathogen belonging to, or classified under, the specified genus.
-
C.
hasTarget
chosen
Indicates that one entity is directed toward, aimed at, or intended to affect another specific entity as its target.
-
D.
pathogenicityToHumans
Indicates that an entity has the capacity to cause disease or harmful health effects in humans.
-
E.
susceptibleTo
Indicates that one entity is vulnerable or likely to be affected, harmed, or influenced by another entity or factor.
- 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_69a4938db1f081909bcd1ad2713b6096 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4acae12948190923d31966c26a130 |
completed | March 1, 2026, 9:16 p.m. |
| PD | Predicate disambiguation | batch_69a4aa8d47c081909b02a53e305ccf7a |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:39 p.m.