Triple
T5194785
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fontaine-de-Vaucluse |
E117242
|
entity |
| Predicate | springFlowCharacteristic |
P36918
|
FINISHED |
| Object | strong seasonal variation |
—
|
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: strong seasonal variation | Statement: [Fontaine-de-Vaucluse, springFlowCharacteristic, strong seasonal variation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: springFlowCharacteristic Context triple: [Fontaine-de-Vaucluse, springFlowCharacteristic, strong seasonal variation]
-
A.
hasFlowRegime
Indicates that one entity is characterized by, or operates under, a particular pattern or regime of flow.
-
B.
flowsFrom
Indicates that a substance, medium, or influence moves or originates from one entity or location and proceeds outward to another.
-
C.
flowsAt
Indicates that a fluid or substance moves through or along a specific location, point, or region.
-
D.
flowVariation
chosen
Indicates how the rate or pattern of flow (such as water, traffic, or data) changes over time or across different conditions.
-
E.
flowsOver
Indicates that one substance or medium moves across the surface or boundary of another, covering or passing above it.
- 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_69bd4462ed04819084fcb01eb9d2fa74 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7adb034c819086bf8a85fbf158f4 |
completed | March 20, 2026, 4:50 p.m. |
| PD | Predicate disambiguation | batch_69bd77b9a67c8190819612257ea746b4 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:46 p.m.