Triple
T28858851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naegleria fowleri |
E728806
|
entity |
| Predicate | treatmentOption |
P4714
|
FINISHED |
| Object | amphotericin B |
—
|
NE NERFINISHED |
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: amphotericin B | Statement: [Naegleria fowleri, treatmentOption, amphotericin B]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: treatmentOption Context triple: [Naegleria fowleri, treatmentOption, amphotericin B]
-
A.
treatmentType
Indicates the specific kind or category of treatment applied or prescribed in relation to an entity or condition.
-
B.
proposedTreatment
Indicates that one entity is suggested or recommended as a possible treatment or therapeutic intervention for another entity.
-
C.
treatmentIndication
Indicates that a treatment is intended to address, alleviate, or prevent a particular condition, symptom, or medical indication.
-
D.
treatment
chosen
Indicates that one entity is used as a medical or therapeutic intervention to address, manage, or cure a condition affecting another entity.
-
E.
treatmentOf
Indicates a relationship where one entity administers, provides, or is responsible for a therapeutic intervention directed toward another entity (typically a patient or condition).
- 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_69f0319f4e5481909e4c439dbe8be940 |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f68805b4848190b75da14996d52a38 |
completed | May 2, 2026, 11:25 p.m. |
| PD | Predicate disambiguation | batch_69f68609c0b08190a8e1238a4d97c270 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 28, 2026, 6:46 a.m.