Triple
T36755903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Perfect Sense |
E908050
|
entity |
| Predicate | hasEpidemicNameInPlot |
P186267
|
FINISHED |
| Object | Severe Olfactory Syndrome |
—
|
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: Severe Olfactory Syndrome | Statement: [Perfect Sense, hasEpidemicNameInPlot, Severe Olfactory Syndrome]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEpidemicNameInPlot Context triple: [Perfect Sense, hasEpidemicNameInPlot, Severe Olfactory Syndrome]
-
A.
hasEpidemicEffect
Indicates that something causes, contributes to, or characterizes the spread and impact of an epidemic.
-
B.
epidemicType
Indicates the classification of an epidemic according to its nature, pattern, or mode of spread.
-
C.
associatedWithEpidemic
Indicates that something has a connection or relevance to an epidemic, such as being caused by, occurring during, or contributing to that epidemic.
-
D.
hasPandemicCause
Indicates that one entity is the underlying cause or origin of a pandemic affecting another entity.
-
E.
hasEpidemiologyFeature
Indicates that an entity possesses a specific epidemiological characteristic or attribute related to the occurrence, distribution, or determinants of health conditions.
- 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_69f76e779bec8190be0e1f87a131e0f4 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7cabacc1481909e839454ce1057f7 |
completed | May 3, 2026, 10:22 p.m. |
| PD | Predicate disambiguation | batch_69f7c8999a348190abc1895eaa6e036d |
completed | May 3, 2026, 10:13 p.m. |
| PDg | Predicate description generation | batch_69f7c9f4c7c48190ba918d8d5dc8dfd9 |
completed | May 3, 2026, 10:19 p.m. |
Created at: May 3, 2026, 4:12 p.m.