Triple
T6462142
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ponte Vecchio |
E142145
|
entity |
| Predicate | hasFloodDamageEvent |
P39409
|
FINISHED |
| Object | 1333 Arno flood |
—
|
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: 1333 Arno flood | Statement: [Ponte Vecchio, hasFloodDamageEvent, 1333 Arno flood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFloodDamageEvent Context triple: [Ponte Vecchio, hasFloodDamageEvent, 1333 Arno flood]
-
A.
hasFloodRisk
Indicates that an entity is exposed to a potential or expected risk of flooding under certain conditions.
-
B.
floodEvent
Indicates an occurrence of a flooding event affecting a location, time period, or set of impacted entities.
-
C.
hasFloodHistory
Indicates that the subject has experienced one or more flood events in the past.
-
D.
notableFloodEvents
chosen
Indicates that there are significant or historically important flood occurrences associated with the given entity.
-
E.
hasSeasonalFlooding
Indicates that an area regularly experiences flooding during specific, recurring times of the year.
- 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_69c008d2f91c8190a8178767a35e08fc |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c069f7e5908190ae4d8da2b14d274f |
completed | March 22, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69c0673d46a08190bc8bcd29f9555fe7 |
completed | March 22, 2026, 10:03 p.m. |
Created at: March 22, 2026, 4:49 p.m.