Triple
T26119196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bonegilla Migrant Reception and Training Centre |
E658909
|
entity |
| Predicate | receivedMigrantsFrom |
P163713
|
FINISHED |
| Object | Displaced persons camps in Europe |
—
|
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: Displaced persons camps in Europe | Statement: [Bonegilla Migrant Reception and Training Centre, receivedMigrantsFrom, Displaced persons camps in Europe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: receivedMigrantsFrom Context triple: [Bonegilla Migrant Reception and Training Centre, receivedMigrantsFrom, Displaced persons camps in Europe]
-
A.
receivedMigrantsFrom
chosen
Indicates that one entity has accepted or taken in migrants originating from another entity.
-
B.
numberOfImmigrantsProcessed
Indicates the total count of immigrants that have been processed in a given context or system.
-
C.
carriedImmigrantsFrom
Indicates that one entity transported immigrants from a specified origin location to another place.
-
D.
estimatedEmigrants
Indicates the estimated number of people who have left a place or country to live elsewhere.
-
E.
receivedAsylumFrom
Indicates that one entity was granted asylum or refuge by another entity, typically a state or institution.
- 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_69ee5bc20298819099a42be042eb2349 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f63fd6c68481908c542aa03e297b9c |
completed | May 2, 2026, 6:17 p.m. |
| PD | Predicate disambiguation | batch_69f63c6456608190b94e7c2e2c2a4824 |
completed | May 2, 2026, 6:03 p.m. |
Created at: April 26, 2026, 8:07 p.m.