Triple
T14739053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fiuggi |
E346294
|
entity |
| Predicate | hasMineralWaterSpring |
P85830
|
FINISHED |
| Object | Fiuggi water |
—
|
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: Fiuggi water | Statement: [Fiuggi, hasMineralWaterSpring, Fiuggi water]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMineralWaterSpring Context triple: [Fiuggi, hasMineralWaterSpring, Fiuggi water]
-
A.
hasMineralSprings
chosen
Indicates that a place or entity possesses or is characterized by the presence of mineral springs.
-
B.
hasMineralSpringsType
Indicates that an entity is associated with or characterized by a specific type or category of mineral springs.
-
C.
hasFreshwaterSprings
Indicates that the subject contains or is associated with natural sources of freshwater emerging from the ground.
-
D.
hasHotSpring
Indicates that one entity possesses, contains, or is associated with a hot spring.
-
E.
hasMineralSpringsTemperatureRange
Indicates the range of temperatures characteristic of the mineral springs 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_69d822e6f1c88190bc494d491a907114 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec73264848190be23c5f0260cbe13 |
completed | April 14, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69de8bf9331481909582045cd567d91f |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:29 a.m.