Triple
T6265029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hurricane Maria |
E140391
|
entity |
| Predicate | fatalitiesRange |
P700
|
FINISHED |
| Object | approximately 3,000–3,100 (direct and indirect) |
—
|
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: approximately 3,000–3,100 (direct and indirect) | Statement: [Hurricane Maria, fatalitiesRange, approximately 3,000–3,100 (direct and indirect)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fatalitiesRange Context triple: [Hurricane Maria, fatalitiesRange, approximately 3,000–3,100 (direct and indirect)]
-
A.
fatalitiesCategory
Indicates the classification of deaths associated with an event, incident, or condition into a specific category or severity level.
-
B.
numberOfVictimsKilled
Indicates the count of victims who were killed as a result of the referenced event or action.
-
C.
deathTollEstimate
chosen
Indicates an estimated number of deaths attributed to a particular event, cause, or period.
-
D.
deathToll
Indicates the number of deaths resulting from a particular event, situation, or cause.
-
E.
casualtiesEstimate
Indicates an estimated number of people killed, injured, or otherwise harmed as a result of 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_69c008cabc4081909723e2547c9d6cc0 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0639e64588190875e4e1e772fb336 |
completed | March 22, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69c05606fb50819082d1a5a91e5030b6 |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:25 p.m.