Triple
T16222290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1746 Lima–Callao earthquake |
E393757
|
entity |
| Predicate | casualtiesInCallao |
P10775
|
FINISHED |
| Object | most of the population of Callao killed |
—
|
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: most of the population of Callao killed | Statement: [1746 Lima–Callao earthquake, casualtiesInCallao, most of the population of Callao killed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: casualtiesInCallao Context triple: [1746 Lima–Callao earthquake, casualtiesInCallao, most of the population of Callao killed]
-
A.
casualtiesImperialSpanish
Indicates that the subject incurred casualties belonging to, or associated with, the Imperial Spanish forces.
-
B.
casualties
Indicates that an event, action, or situation resulted in people being killed or injured.
-
C.
nativeCasualties
Indicates that native or indigenous people suffered deaths or injuries as a result of a particular event, action, or conflict.
-
D.
casualtiesAssociatedWithEvent
Indicates that certain casualties (deaths or injuries) are linked to, or resulted from, a specific event.
-
E.
casualtiesDescription
chosen
Indicates a textual description of the human losses (such as deaths, injuries, or missing persons) resulting from an event or incident.
- 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_69d87f204df88190a8f88923decf9835 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e227fcf058819099d5ff965cc2c267 |
completed | April 17, 2026, 12:30 p.m. |
| PD | Predicate disambiguation | batch_69e219e94a448190b73a4e6aa374eb4a |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:03 a.m.