Triple
T5943619
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rivoli |
E132226
|
entity |
| Predicate | urbanAreaRelation |
P37938
|
FINISHED |
| Object | suburban area of Turin |
—
|
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: suburban area of Turin | Statement: [Rivoli, urbanAreaRelation, suburban area of Turin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: urbanAreaRelation Context triple: [Rivoli, urbanAreaRelation, suburban area of Turin]
-
A.
arealRegion
Indicates that something occupies or pertains to a specific two-dimensional geographic or spatial area.
-
B.
urbanAreaType
Indicates the classification of an area based on its urban characteristics or development type (e.g., city, town, suburb, metropolitan region).
-
C.
regionOfCity
chosen
Indicates that a specified area or district is a constituent part or subdivision of a particular city.
-
D.
formsUrbanAreaWith
Indicates that two or more settlements are geographically and functionally connected so that together they constitute a single continuous urban area.
-
E.
administrativeDistrictOf
Indicates that one entity serves as the administrative district or jurisdictional area governing or encompassing another 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_69c00869d3308190af89b2453e0f7546 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c03ee10b308190afe38b904ae7c5f7 |
completed | March 22, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69c0335806788190b6488ca8b73f7a63 |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 4:01 p.m.