Triple
T1399421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Middle Passage |
E30745
|
entity |
| Predicate | estimatedMortalityRate |
P4715
|
FINISHED |
| Object | between 10 and 20 percent |
—
|
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: between 10 and 20 percent | Statement: [Middle Passage, estimatedMortalityRate, between 10 and 20 percent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estimatedMortalityRate Context triple: [Middle Passage, estimatedMortalityRate, between 10 and 20 percent]
-
A.
mortalityRate
chosen
Indicates the proportion of individuals in a defined population that die within a specified time period.
-
B.
caseFatalityRate
Indicates the proportion of deaths among all identified cases of a particular disease or condition within a specified period.
-
C.
deathTollEstimate
Indicates an estimated number of deaths attributed to a particular event, cause, or period.
-
D.
casualtiesEstimate
Indicates an estimated number of people killed, injured, or otherwise harmed as a result of an event or incident.
-
E.
deathToll
Indicates the number of deaths resulting from a particular event, situation, or cause.
- 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_69a498fd4e408190bd73eca30ea9754c |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c39b1ea0819090e49454885d4b7d |
completed | March 1, 2026, 10:54 p.m. |
| PD | Predicate disambiguation | batch_69a4bf017f8081908572121560ec621f |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:59 p.m.