Triple
T18907796
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metropolitan area of Padua |
E462509
|
entity |
| Predicate | hasCommuterBelt |
P133745
|
FINISHED |
| Object | municipalities surrounding Padua |
—
|
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: municipalities surrounding Padua | Statement: [Metropolitan area of Padua, hasCommuterBelt, municipalities surrounding Padua]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommuterBelt Context triple: [Metropolitan area of Padua, hasCommuterBelt, municipalities surrounding Padua]
-
A.
hasPhysicalBelt
Indicates that one entity possesses or is equipped with a physical belt as an item or feature.
-
B.
usesBeltSystem
Indicates that a subject employs a structured belt-ranking system (e.g., colored belts) to denote levels of skill, progress, or status.
-
C.
commuterBrand
Indicates a relationship where a brand is specifically associated with or targeted toward commuter use or commuting contexts.
-
D.
hasCommuterPattern
Indicates that there is a characteristic or recurring pattern in how an entity regularly travels between locations, typically for work or daily activities.
-
E.
isCommuterHub
Indicates that a location functions as a central node where many commuters start, end, or transfer during their regular travel.
- 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_69d8dcfd05bc819088903cca13cc2846 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c52dcb948190a5b6a783512bf7d6 |
completed | April 20, 2026, 6:18 a.m. |
| PD | Predicate disambiguation | batch_69e4a2e9e6488190ba8df92c8058ed88 |
completed | April 19, 2026, 9:39 a.m. |
| PDg | Predicate description generation | batch_69e4ad8e075c8190ad561edc5e520057 |
completed | April 19, 2026, 10:25 a.m. |
Created at: April 10, 2026, 11:58 a.m.