Triple
T21081096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St Non’s Chapel and Well |
E519369
|
entity |
| Predicate | wellWaterReputedFor |
P142759
|
FINISHED |
| Object | healing properties |
—
|
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: healing properties | Statement: [St Non’s Chapel and Well, wellWaterReputedFor, healing properties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wellWaterReputedFor Context triple: [St Non’s Chapel and Well, wellWaterReputedFor, healing properties]
-
A.
waterSourceDedicatedTo
Indicates that a particular water source is specifically allocated or reserved for a designated use, group, or purpose.
-
B.
waterSourceType
Indicates the kind or category of source from which water is obtained.
-
C.
waterSource
Indicates that one entity serves as the source or provider of water for another entity.
-
D.
waterOrigin
Indicates the source or starting location from which the water originates or is supplied.
-
E.
waterType
Indicates the specific kind or category of water associated with an entity (e.g., fresh, salt, brackish).
- 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_69e0b506e59c8190849b71ed07929215 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e702db430c81908a1547d8fbe45506 |
completed | April 21, 2026, 4:53 a.m. |
| PD | Predicate disambiguation | batch_69e5dbfcd5e881908f1e4e0d2d237856 |
completed | April 20, 2026, 7:55 a.m. |
| PDg | Predicate description generation | batch_69e5e2e03d88819086f8b641656ad8b0 |
completed | April 20, 2026, 8:25 a.m. |
Created at: April 16, 2026, 2:49 p.m.