Triple
T34200489
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SS Mendi |
E877365
|
entity |
| Predicate | victimsNumberApproximate |
P150701
|
FINISHED |
| Object | over 600 |
—
|
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: over 600 | Statement: [SS Mendi, victimsNumberApproximate, over 600]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: victimsNumberApproximate Context triple: [SS Mendi, victimsNumberApproximate, over 600]
-
A.
hasApproximateNumberOfVictims
chosen
Indicates that an entity is associated with an estimated, non-exact count of victims.
-
B.
estimatedVictimsLowerBound
Indicates the minimum estimated number of victims associated with an event, entity, or incident.
-
C.
numberOfSuspectedVictims
Indicates the count of individuals believed or alleged to be victims in a particular incident, case, or context.
-
D.
estimatedVictimsUpperBound
Indicates the maximum estimated number of victims associated with an event, incident, or situation.
-
E.
numberOfVictimsConfirmed
Indicates the confirmed count of victims associated with an event, incident, or situation.
- 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_69f349aff5f0819096275315abea5344 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f7102baf8081908c23da0e99710d85 |
completed | May 3, 2026, 9:06 a.m. |
| PD | Predicate disambiguation | batch_69f70f3c5bfc81908585f52e196dafe5 |
completed | May 3, 2026, 9:02 a.m. |
Created at: May 1, 2026, 1:55 a.m.