Triple
T4136909
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chernobyl disaster |
E85175
|
entity |
| Predicate | estimatedAffectedPeople |
P54084
|
FINISHED |
| Object | hundreds of thousands |
—
|
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: hundreds of thousands | Statement: [Chernobyl disaster, estimatedAffectedPeople, hundreds of thousands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estimatedAffectedPeople Context triple: [Chernobyl disaster, estimatedAffectedPeople, hundreds of thousands]
-
A.
estimatedVictimsUnderAuthority
Indicates that a specified authority is estimated to have a certain number of victims under its control, influence, or jurisdiction.
-
B.
estimatedNumberOfPeopleSaved
Indicates the approximate count of individuals whose lives were preserved or harm was averted as a result of a particular action, intervention, or entity.
-
C.
numberOfSuspectedVictims
Indicates the count of individuals believed or alleged to be victims in a particular incident, case, or context.
-
D.
affectedPerson
Indicates that a particular person is impacted or influenced by an event, action, or condition.
-
E.
supportedPopulation
Indicates that one entity provides assistance, resources, or services to sustain or benefit a specified group of people.
- 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_69aed935ccd881909dc61f81bcdb7a78 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af03a0f3408190adba7a8513bd3d12 |
completed | March 9, 2026, 5:30 p.m. |
| PD | Predicate disambiguation | batch_69af018a54848190987f18c066c75068 |
completed | March 9, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69af039fb19c8190b20e62a3b3ad25c1 |
completed | March 9, 2026, 5:30 p.m. |
Created at: March 9, 2026, 3:43 p.m.