Triple
T610990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tiber |
E12096
|
entity |
| Predicate | hasFloodHistory |
P17084
|
FINISHED |
| Object | frequent historical flooding in Rome |
—
|
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: frequent historical flooding in Rome | Statement: [Tiber, hasFloodHistory, frequent historical flooding in Rome]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFloodHistory Context triple: [Tiber, hasFloodHistory, frequent historical flooding in Rome]
-
A.
hasFloodRisk
Indicates that an entity is exposed to a potential or expected risk of flooding under certain conditions.
-
B.
hasFloodProtectionProject
Indicates that a flood protection project exists or is implemented for the referenced entity.
-
C.
hasFloodplain
Indicates that an area or location lies within the floodplain associated with a particular water body or flooding source.
-
D.
hasSeasonalFlooding
Indicates that an area regularly experiences flooding during specific, recurring times of the year.
-
E.
hasWaterQualityHistory
Indicates that an entity is associated with a record or series of records describing changes or measurements of its water quality over time.
- F. None of above. chosen
Provenance (4 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_69a493309df48190a327f748e88049a6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49df7c088819082eb70de4f0f4fbf |
completed | March 1, 2026, 8:13 p.m. |
| PD | Predicate disambiguation | batch_69a49cfa7b4481909bec7a5fd3e98c65 |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49def31ec81909dc53e70f4a36eda |
completed | March 1, 2026, 8:13 p.m. |
Created at: March 1, 2026, 7:35 p.m.