Triple
T282291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hungarian Revolution of 1956 |
E5378
|
entity |
| Predicate | approximateRefugeeNumber |
P1943
|
FINISHED |
| Object | 200000 |
—
|
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: 200000 | Statement: [Hungarian Revolution of 1956, approximateRefugeeNumber, 200000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateRefugeeNumber Context triple: [Hungarian Revolution of 1956, approximateRefugeeNumber, 200000]
-
A.
displacedPeopleEstimate
chosen
Indicates an estimated number of people who have been forced to leave their homes or usual places of residence due to a particular event or situation.
-
B.
hasPopulationApproximate
Indicates that an entity has an estimated or approximate population size, rather than an exact count.
-
C.
immigrantPopulationShare
Indicates the proportion of a total population that is made up of immigrants.
-
D.
civilianDisplacement
Indicates the forced or compelled movement of civilian populations from their homes or usual places of residence, typically due to conflict, violence, or persecution.
-
E.
militaryCasualtiesEstimate
Indicates an estimated number of people killed, wounded, or missing as a result of military conflict or operations.
- 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_69a257e6c8788190987dfe705ca2912a |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25e0c14b48190a5c936bab36180b3 |
completed | Feb. 28, 2026, 3:16 a.m. |
| PD | Predicate disambiguation | batch_69a25b77e028819087e606fc321219f7 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:59 a.m.