Triple
T4237007
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hungnam evacuation |
E94717
|
entity |
| Predicate | numberOfEvacuatedVehicles |
P22510
|
FINISHED |
| Object | approximately 17000 |
—
|
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: approximately 17000 | Statement: [Hungnam evacuation, numberOfEvacuatedVehicles, approximately 17000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfEvacuatedVehicles Context triple: [Hungnam evacuation, numberOfEvacuatedVehicles, approximately 17000]
-
A.
numberOfEvacuated
Indicates the total count of individuals who have been evacuated from a location or situation.
-
B.
numberOfVehicles
chosen
Indicates the total count of vehicles associated with a given entity or context.
-
C.
evacuatedBy
Indicates that an entity is removed or cleared from a place or situation through the action or assistance of another agent or process.
-
D.
numberOfPassengerCars
Indicates the total count of passenger cars associated with or contained in a given entity or context.
-
E.
axisForcesEvacuatedFrom
Indicates that Axis forces were compelled to withdraw or be removed from a particular location or area.
- 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_69b34537cc6481909cd0a96acbb33ef7 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34e7422a88190955f5f4347fa80d2 |
completed | March 12, 2026, 11:38 p.m. |
| PD | Predicate disambiguation | batch_69b347f3bd188190b0cd613e8a5c1683 |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:05 p.m.