Triple
T397170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Operation Crossroads |
E9207
|
entity |
| Predicate | effectOnPopulation |
P3838
|
FINISHED |
| Object | displacement of Bikini Atoll inhabitants |
—
|
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: displacement of Bikini Atoll inhabitants | Statement: [Operation Crossroads, effectOnPopulation, displacement of Bikini Atoll inhabitants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectOnPopulation Context triple: [Operation Crossroads, effectOnPopulation, displacement of Bikini Atoll inhabitants]
-
A.
demographicImpact
chosen
Indicates how an action, event, or condition affects the size, structure, or composition of a population.
-
B.
supportsPopulation
Indicates that one entity provides the necessary conditions or resources for a population of another entity to exist, persist, or thrive.
-
C.
populationIncrease
Indicates that the number of individuals in a population has grown over a specified period of time.
-
D.
supportedPopulation
Indicates that one entity provides assistance, resources, or services to sustain or benefit a specified group of people.
-
E.
hasPopulationType
Indicates that an entity’s population is classified according to a specific type or category (e.g., demographic, biological, or statistical grouping).
- 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_69a2e8004cb88190b92ed1add6abf41a |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2ec8a941081909a152fda0ce24a98 |
completed | Feb. 28, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69a2e96d17d08190878d3a68b17d51ca |
completed | Feb. 28, 2026, 1:11 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.