Triple
T29392317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sleeping Beauties television series (in development) |
E745398
|
entity |
| Predicate | hasEpidemicEffect |
P167143
|
FINISHED |
| Object | puts women to sleep |
—
|
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: puts women to sleep | Statement: [Sleeping Beauties television series (in development), hasEpidemicEffect, puts women to sleep]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEpidemicEffect Context triple: [Sleeping Beauties television series (in development), hasEpidemicEffect, puts women to sleep]
-
A.
epidemicImpact
Indicates the extent and nature of how an epidemic affects entities, such as populations, regions, or systems.
-
B.
associatedWithEpidemic
Indicates that something has a connection or relevance to an epidemic, such as being caused by, occurring during, or contributing to that epidemic.
-
C.
epidemicType
Indicates the classification of an epidemic according to its nature, pattern, or mode of spread.
-
D.
hasPandemicCause
Indicates that one entity is the underlying cause or origin of a pandemic affecting another entity.
-
E.
epidemicScale
Indicates that an event, condition, or phenomenon occurs with such widespread prevalence and rapid spread that it reaches an epidemic level in scale.
- 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_69f0a79dfabc81908755382ee47791e2 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f669fff6488190ae591e1c99dfeed8 |
completed | May 2, 2026, 9:17 p.m. |
| PD | Predicate disambiguation | batch_69f66339175c819080bd70f0ff7057b1 |
completed | May 2, 2026, 8:48 p.m. |
| PDg | Predicate description generation | batch_69f663ff176c8190aaadb475f75daee4 |
completed | May 2, 2026, 8:52 p.m. |
Created at: April 28, 2026, 2:43 p.m.