Triple
T37965040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Tauro |
E947116
|
entity |
| Predicate | hasModernMunicipalityOnSlopes |
P39554
|
FINISHED |
| Object | Taormina |
—
|
NE NERFINISHED |
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: Taormina | Statement: [Mount Tauro, hasModernMunicipalityOnSlopes, Taormina]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasModernMunicipalityOnSlopes Context triple: [Mount Tauro, hasModernMunicipalityOnSlopes, Taormina]
-
A.
hasMajorCityOnSlopes
Indicates that a major city is located on the slopes of the referenced geographic feature (such as a mountain or hill).
-
B.
hasProtectedAreaOnSlopes
Indicates that a designated protected area exists specifically on the slopes of a landform or terrain.
-
C.
hasSettlementOnSlopes
chosen
Indicates that a settlement is located on or extends across the slopes of a landform such as a hill or mountain.
-
D.
hasForestedSlopes
Indicates that the subject has slopes that are covered predominantly with forest or woodland vegetation.
-
E.
isMountainMunicipality
Indicates that a municipality is classified as being located in a mountainous area or characterized by predominantly mountainous terrain.
- 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_69f76ef7062c819091bfacb7e83aa1e0 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69ffbb1c5bf88190a0bf791213045885 |
completed | May 9, 2026, 10:54 p.m. |
| PD | Predicate disambiguation | batch_69ffba0ab0f881908f84ef81f7a1bfe8 |
completed | May 9, 2026, 10:49 p.m. |
Created at: May 3, 2026, 4:20 p.m.