Triple
T3210799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parícutin |
E67274
|
entity |
| Predicate | casualtiesCause |
P144
|
FINISHED |
| Object | lightning associated with eruption |
—
|
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: lightning associated with eruption | Statement: [Parícutin, casualtiesCause, lightning associated with eruption]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: casualtiesCause Context triple: [Parícutin, casualtiesCause, lightning associated with eruption]
-
A.
casualties
Indicates that an event, action, or situation resulted in people being killed or injured.
-
B.
casualtiesType
Indicates the specific category or nature of casualties (e.g., killed, injured, missing) associated with an event or incident.
-
C.
casualtiesImpact
Indicates how the number or severity of casualties affects or influences another factor, situation, or outcome.
-
D.
casualtiesDescription
Indicates a textual description of the human losses (such as deaths, injuries, or missing persons) resulting from an event or incident.
-
E.
causeOfDeath
chosen
Indicates the specific factor, event, or condition that directly resulted in an entity’s death.
- 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_69ad858ac36c81909962589cd277d6e2 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaab886c48190b72e36d0ac855ffe |
completed | March 8, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69ad9e09b83881908801d79c3d9254f9 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:07 p.m.