Triple
T578729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Black Death |
E15012
|
entity |
| Predicate | hasSymptom |
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: [Black Death, hasSymptom, fever]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSymptom Context triple: [Black Death, hasSymptom, fever]
-
A.
hasHealthConcern
Indicates that an entity has a specific health-related issue, condition, or concern associated with it.
-
B.
symptom
chosen
Indicates that a particular condition, disease, or problem manifests through a specific observable sign or complaint.
-
C.
diagnosedWith
Indicates that a subject has been identified, typically by a medical professional, as having a particular disease or medical condition.
-
D.
has
Indicates that one entity possesses, owns, contains, or includes another entity as part of its state or composition.
-
E.
hasPatient
Indicates that an action, event, or process involves a specific entity as the one undergoing or receiving its effects (the patient).
- 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_69a4935783b8819082b77726ec10cc42 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49b6c358081908f458b9e3e208c0d |
completed | March 1, 2026, 8:02 p.m. |
| PD | Predicate disambiguation | batch_69a494c692288190b88f30299516b5ba |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:33 p.m.