Triple
T30947005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belgrano Norte Line |
E788421
|
entity |
| Predicate | suburbsServed |
P46405
|
FINISHED |
| Object | northern suburbs of Buenos Aires |
—
|
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: northern suburbs of Buenos Aires | Statement: [Belgrano Norte Line, suburbsServed, northern suburbs of Buenos Aires]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: suburbsServed Context triple: [Belgrano Norte Line, suburbsServed, northern suburbs of Buenos Aires]
-
A.
servesSuburbsOf
chosen
Indicates that a service, route, or facility provides coverage or support to the suburban areas associated with a particular city or region.
-
B.
majorSuburbsIncluded
Indicates that certain major suburbs are encompassed within or form part of a larger defined area or entity.
-
C.
townServed
Indicates that a given service, facility, or infrastructure serves or provides coverage to a particular town.
-
D.
hasSuburbanService
Indicates that an entity provides or is connected to a public transportation service specifically serving suburban areas, typically linking suburbs with urban centers.
-
E.
nearbyCityServed
Indicates that a city is geographically close enough to another city to be considered within its service or support area.
- 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_69f224c180f88190ad177372ee02b7e2 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6953bafb88190a860e9c68a3dd4b2 |
completed | May 3, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69f690ed5d008190831cf8e44cce28af |
completed | May 3, 2026, 12:03 a.m. |
Created at: April 29, 2026, 8:53 p.m.