Triple
T2708231
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bikini Atoll |
E59794
|
entity |
| Predicate | resettlementHaltedDueTo |
P3057
|
FINISHED |
| Object | radiation levels |
—
|
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: radiation levels | Statement: [Bikini Atoll, resettlementHaltedDueTo, radiation levels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: resettlementHaltedDueTo Context triple: [Bikini Atoll, resettlementHaltedDueTo, radiation levels]
-
A.
majorResettlementArea
Indicates that a location serves as a primary or significant destination area where people are being resettled.
-
B.
settledAfterDeportationIn
Indicates that an entity established residence in a place following its deportation or forced removal.
-
C.
usedToRestrictEmigrationTo
Indicates that an entity implemented measures or policies to limit or control people leaving a particular place or jurisdiction.
-
D.
usedToRestrictEmigrationFrom
Indicates that something was employed as a means to limit or control people leaving a particular place or country.
-
E.
reasonForRelocation
chosen
Indicates the underlying cause, motivation, or circumstance that led an entity to move from one location to another.
- 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_69ab4ac92a088190bc74bca14038e3de |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abda73de1c81908f5d6b0383e23144 |
completed | March 7, 2026, 7:57 a.m. |
| PD | Predicate disambiguation | batch_69abd8224c688190bb4a362360b03007 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:55 p.m.