Triple
T19772976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prevnar 13 |
E474933
|
entity |
| Predicate | protectsAgainstSerotypeCount |
P137278
|
FINISHED |
| Object | 13 |
—
|
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: 13 | Statement: [Prevnar 13, protectsAgainstSerotypeCount, 13]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: protectsAgainstSerotypeCount Context triple: [Prevnar 13, protectsAgainstSerotypeCount, 13]
-
A.
includesSerotype
Indicates that one entity contains or encompasses a specific serotype as part of its defined set or composition.
-
B.
providesProtectionAgainst
Indicates that one entity serves to guard, shield, or defend another entity from a specified harm, threat, or adverse effect.
-
C.
immunityType
Indicates the specific kind or category of immunity that applies in a given context (e.g., legal, diplomatic, medical).
-
D.
serogroup
Indicates that entities are grouped or classified together based on sharing the same serological (antigenic) characteristics.
-
E.
numberOfInletsProtected
Indicates the quantity of inlets that are safeguarded or protected by the specified object or system.
- F. None of above. chosen
Provenance (4 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_69d8e51a43a08190956bc6df13c91a77 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6535e450c8190a2628245ae0d0bd3 |
completed | April 20, 2026, 4:25 p.m. |
| PD | Predicate disambiguation | batch_69e53053ed2881908400becdfada7fd3 |
completed | April 19, 2026, 7:43 p.m. |
| PDg | Predicate description generation | batch_69e532bbedf081908d801600e2af94a7 |
completed | April 19, 2026, 7:53 p.m. |
Created at: April 10, 2026, 1:48 p.m.