Triple
T8729057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abano Terme |
E207205
|
entity |
| Predicate | usesMud |
P84303
|
FINISHED |
| Object | therapeutic mud from local hot springs |
—
|
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: therapeutic mud from local hot springs | Statement: [Abano Terme, usesMud, therapeutic mud from local hot springs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesMud Context triple: [Abano Terme, usesMud, therapeutic mud from local hot springs]
-
A.
usesMagic
Indicates that an entity performs actions or achieves effects by employing magical powers or supernatural abilities.
-
B.
usesMagicFor
Indicates that one entity employs or applies magic as a means to achieve, affect, or perform something involving another entity or context.
-
C.
stoneUse
Indicates that one entity uses or employs stone as a material or tool for some purpose or activity.
-
D.
usedAgainst
Indicates that one entity is employed, applied, or deployed in opposition to, or for the purpose of affecting, another entity.
-
E.
usesModerator
Indicates that an entity employs or relies on a moderator to oversee, regulate, or manage its interactions or processes.
- 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_69ca8358e4008190898471a59b96c301 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d19fdc88190860e0c9c93ab79ce |
completed | March 31, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_69cc457093188190959287a6458651c6 |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc489dd528819084ed5d88bd8bb3d6 |
completed | March 31, 2026, 10:20 p.m. |
Created at: March 30, 2026, 6:37 p.m.