Triple
T705343
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arlington, Massachusetts |
E14085
|
entity |
| Predicate | hasPublicTransportation |
P941
|
FINISHED |
| Object | MBTA bus service |
—
|
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: MBTA bus service | Statement: [Arlington, Massachusetts, hasPublicTransportation, MBTA bus service]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPublicTransportation Context triple: [Arlington, Massachusetts, hasPublicTransportation, MBTA bus service]
-
A.
hasPublicTransportConnection
Indicates that there is an available public transportation link or service connecting the related entities.
-
B.
hasPublicTransportStop
Indicates that a location or area contains or is served by a public transport stop, such as a bus, tram, or train stop.
-
C.
hasTransportRoute
Indicates that there exists a designated transportation connection or route linking one entity to another.
-
D.
hasTransportationSystem
chosen
Indicates that an entity possesses, operates, or is served by an organized system for transporting people or goods.
-
E.
hasTramway
Indicates that a location or area is served by, contains, or is connected to a tramway system.
- 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_69a493494ec48190ae6751683625a9ba |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a58d4c3c8190ad4527d14bca5e6e |
completed | March 1, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69a4a4edc33881909a978268f6dd5d82 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:36 p.m.