Triple
T25265279
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Struma |
E633412
|
entity |
| Predicate | numberOfRefugeesOnBoardApprox |
P23315
|
FINISHED |
| Object | around 769 |
—
|
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: around 769 | Statement: [Struma, numberOfRefugeesOnBoardApprox, around 769]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfRefugeesOnBoardApprox Context triple: [Struma, numberOfRefugeesOnBoardApprox, around 769]
-
A.
approximateNumberOfRefugeesTransported
chosen
Indicates an estimated count of refugees who were transported in the described event or context.
-
B.
refugeeTransportShip
Indicates a ship whose primary role is to carry or evacuate refugees from one location to another.
-
C.
hasRefugeePopulation
Indicates that an entity hosts, contains, or is associated with a population of refugees.
-
D.
lifeboatCapacity
Indicates the maximum number of people or load that a lifeboat is designed and certified to safely carry.
-
E.
carriedImmigrantsTo
Indicates that one entity transported immigrants from one place 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_69e75a922ad481908f4f1f884583cb42 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f70e8755a48190931eaa77946f9460 |
completed | May 3, 2026, 8:59 a.m. |
| PD | Predicate disambiguation | batch_69f70abc00848190a1c3f495ef6c8dc6 |
completed | May 3, 2026, 8:43 a.m. |
Created at: April 21, 2026, 1:14 p.m.