Triple
T37393822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2016 Ellicott City flood |
E928792
|
entity |
| Predicate | mainTypeOfDamage |
P22116
|
FINISHED |
| Object | flash flooding |
—
|
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: flash flooding | Statement: [2016 Ellicott City flood, mainTypeOfDamage, flash flooding]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainTypeOfDamage Context triple: [2016 Ellicott City flood, mainTypeOfDamage, flash flooding]
-
A.
primaryDamageType
chosen
Indicates the main kind of harm or injury that an action, event, or object is responsible for causing.
-
B.
hasTypeOfDamage
Indicates that an entity experiences or exhibits a specific kind or category of damage.
-
C.
damageTo
Indicates a relationship where one entity causes harm, loss, or deterioration to another entity.
-
D.
damageClass
Indicates the type or category of damage associated with an action, event, or interaction between entities.
-
E.
typeOfDam
Indicates the specific kind or classification of a dam associated with an entity.
- 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_69f76ebb10c481909b54b9dba263e29f |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fd19f791f48190bbb6f6047f9ddc59 |
completed | May 7, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69fd0df365948190bc9bfc7ffd46acd8 |
completed | May 7, 2026, 10:10 p.m. |
Created at: May 3, 2026, 4:16 p.m.