Triple
T3473526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Third Plague Pandemic |
E73317
|
entity |
| Predicate | peakImpact |
P42250
|
FINISHED |
| Object | late 19th century |
—
|
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: late 19th century | Statement: [Third Plague Pandemic, peakImpact, late 19th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: peakImpact Context triple: [Third Plague Pandemic, peakImpact, late 19th century]
-
A.
impactBuilding
Indicates that one entity physically collides with or strikes a building, causing an impact event.
-
B.
impactEvent
Indicates that one entity physically strikes or collides with another, producing a resulting effect or change.
-
C.
impactOnLeader
Indicates that one entity has an effect, influence, or consequence on a leader within a given context.
-
D.
impactOnMarket
Indicates the effect or influence that one factor, event, or action has on market conditions, behavior, or outcomes.
-
E.
majorImpact
chosen
Indicates that one entity has a significant, highly influential, or transformative effect on another entity or outcome.
- 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_69ad85b2fed48190948c8765e453d270 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbb3e03e081908aa09291bbf351bd |
completed | March 8, 2026, 6:09 p.m. |
| PD | Predicate disambiguation | batch_69adae07802c8190919c49b0e65b2797 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:17 p.m.