Triple
T16222291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1746 Lima–Callao earthquake |
E393757
|
entity |
| Predicate | casualtiesInLima |
P122222
|
FINISHED |
| Object | several thousand deaths |
—
|
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: several thousand deaths | Statement: [1746 Lima–Callao earthquake, casualtiesInLima, several thousand deaths]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: casualtiesInLima Context triple: [1746 Lima–Callao earthquake, casualtiesInLima, several thousand deaths]
-
A.
casualtiesArgentineKilled
Indicates that the relationship specifies the number of Argentine casualties who were killed in a particular event or context.
-
B.
casualtiesMexicanKilled
Indicates that the event or action resulted in Mexican individuals being killed as casualties.
-
C.
numberOfPanAm103FatalitiesOnGround
Indicates the number of people on the ground who were killed as a result of the Pan Am Flight 103 incident.
-
D.
casualtiesGrenadianAndCuban
Indicates that the relationship involves casualties suffered by both Grenadian and Cuban parties in a given event or context.
-
E.
casualtiesHijackers
Indicates that the hijackers caused or were responsible for casualties (deaths or injuries) among others.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69e21e55a2388190b29a045a8c608ba4 |
completed | April 17, 2026, 11:49 a.m. |
Created at: April 10, 2026, 5:03 a.m.