Triple
T17396267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2007 Ebola outbreak in Democratic Republic of the Congo |
E422961
|
entity |
| Predicate | symptoms |
P2896
|
FINISHED |
| Object | fever |
—
|
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: fever | Statement: [2007 Ebola outbreak in Democratic Republic of the Congo, symptoms, fever]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: symptoms Context triple: [2007 Ebola outbreak in Democratic Republic of the Congo, symptoms, fever]
-
A.
viewsSymptoms
Indicates that one entity observes or examines the symptoms associated with another entity.
-
B.
symptom
chosen
Indicates that a particular condition, disease, or problem manifests through a specific observable sign or complaint.
-
C.
symptomAssociatedWithInfection
Indicates that a particular symptom is linked to, or commonly occurs as a result of, a specific infection.
-
D.
isUsedForSymptom
Indicates that something (such as a treatment, medication, or intervention) is employed to address, alleviate, or manage a particular symptom.
-
E.
clinicalSignOf
Indicates that one clinical sign is evidence or manifestation of a particular disease, condition, or underlying medical state.
- 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_69d889d710288190bf0f4762801fefae |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43abd9b748190bd55c863276d9e3a |
completed | April 19, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69e3b02e6cc88190986e85e64ce9383e |
completed | April 18, 2026, 4:24 p.m. |
Created at: April 10, 2026, 5:45 a.m.