Triple
T7086410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Croatian War of Independence |
E165085
|
entity |
| Predicate | hasDisplacedPersons |
P707
|
FINISHED |
| Object | hundreds of thousands displaced |
—
|
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 displaced | Statement: [Croatian War of Independence, hasDisplacedPersons, hundreds of thousands displaced]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDisplacedPersons Context triple: [Croatian War of Independence, hasDisplacedPersons, hundreds of thousands displaced]
-
A.
displacedBy
Indicates that one entity has been moved, replaced, or forced out of its original position, role, or state by another entity.
-
B.
numberOfEvacuated
Indicates the total count of individuals who have been evacuated from a location or situation.
-
C.
civilianDisplacement
chosen
Indicates the forced or compelled movement of civilian populations from their homes or usual places of residence, typically due to conflict, violence, or persecution.
-
D.
hasVictims
Indicates that an entity has one or more individuals who have been harmed, injured, or adversely affected by it.
-
E.
hasInjuredPerson
Indicates that an entity has a person who has been harmed or injured associated with it.
- 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_69c6887d98408190912b9580666b0c1d |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e512bda88190920ecb54b177e569 |
completed | March 27, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c172148190bf290c07bf579d1f |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:41 p.m.