Triple
T4200644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1918 influenza pandemic |
E86055
|
entity |
| Predicate | disproportionatelyAffected |
P51941
|
FINISHED |
| Object | young adults aged 20 to 40 |
—
|
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: young adults aged 20 to 40 | Statement: [1918 influenza pandemic, disproportionatelyAffected, young adults aged 20 to 40]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: disproportionatelyAffected Context triple: [1918 influenza pandemic, disproportionatelyAffected, young adults aged 20 to 40]
-
A.
discriminatedAgainst
Indicates that one entity treats another unfairly or unequally based on a particular characteristic, such as race, gender, or other protected attributes.
-
B.
hadRepresentationDisproportionateToPopulation
chosen
Indicates that the representation of a group or entity was not proportional to its share of the overall population.
-
C.
affectedPerson
Indicates that a particular person is impacted or influenced by an event, action, or condition.
-
D.
affectedProvision
Indicates that a particular legal provision is impacted, modified, or influenced by another action, decision, or provision.
-
E.
affectedEthnicGroup
Indicates that a particular ethnic group is impacted or influenced by an event, condition, policy, or action.
- 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_69aed93b89f48190a31f6d57c760e42f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af0363bbb8819093f396afe91972e2 |
completed | March 9, 2026, 5:29 p.m. |
| PD | Predicate disambiguation | batch_69af01959c4881909eb1adcb3bdadbe6 |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:49 p.m.