Triple
T7851196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Plata, Maryland |
E182056
|
entity |
| Predicate | eventTypeOf2002Tornado |
P64317
|
FINISHED |
| Object | F4 tornado |
—
|
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: F4 tornado | Statement: [La Plata, Maryland, eventTypeOf2002Tornado, F4 tornado]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eventTypeOf2002Tornado Context triple: [La Plata, Maryland, eventTypeOf2002Tornado, F4 tornado]
-
A.
tornado2011Description
Indicates that the entity provides a textual description or summary of the 2011 tornado event.
-
B.
tornadoIntensity2011
Indicates the intensity level associated with a tornado event that occurred in 2011.
-
C.
typicalStormType
Indicates the kind of storm that is most commonly or characteristically associated with a given context or location.
-
D.
Tornado ADV
Indicates that the action or event occurs in the manner of, or under conditions characterized by, a tornado (e.g., violently, turbulently, or with tornado-like intensity).
-
E.
notableDisasterType
chosen
Indicates the specific kind or category of disaster for which something (such as a place, event, or entity) is notable or best known.
- 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_69ca82869ee08190b8f9040dbc2c0467 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb18eaac508190bf373b1d50b52e1e |
completed | March 31, 2026, 12:44 a.m. |
| PD | Predicate disambiguation | batch_69cae92180f88190ae3d44c3de7adc93 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:50 p.m.