Triple
T6688119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joplin, Missouri |
E152150
|
entity |
| Predicate | tornado2011Fatalities |
P1785
|
FINISHED |
| Object | over 150 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: over 150 deaths | Statement: [Joplin, Missouri, tornado2011Fatalities, over 150 deaths]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tornado2011Fatalities Context triple: [Joplin, Missouri, tornado2011Fatalities, over 150 deaths]
-
A.
regionAffectedByNamedStorms
Indicates that a geographic region is impacted or influenced by one or more specifically named storms.
-
B.
deathToll
chosen
Indicates the number of deaths resulting from a particular event, situation, or cause.
-
C.
worstAffectedStatesByFatalities
Indicates a relationship where certain states are identified as those most severely impacted, ranked highest by the number of fatalities.
-
D.
deathTollEstimate
Indicates an estimated number of deaths attributed to a particular event, cause, or period.
-
E.
strongestStorm
Indicates that one storm is the most intense or powerful compared to a set of other storms.
- 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_69c687f9977c819097e7f5ada4fe522e |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6cd0fa5188190a23281cb09d98139 |
completed | March 27, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69c6ad0d3c1081908dadff7a6a054123 |
completed | March 27, 2026, 4:15 p.m. |
Created at: March 27, 2026, 2:04 p.m.