Triple
T1551733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central station (MBTA) |
E33105
|
entity |
| Predicate | hasRouteMaps |
P31160
|
FINISHED |
| Object | MBTA system maps |
—
|
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 system maps | Statement: [Central station (MBTA), hasRouteMaps, MBTA system maps]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRouteMaps Context triple: [Central station (MBTA), hasRouteMaps, MBTA system maps]
-
A.
hasRoute
Indicates that there exists a path or connection enabling travel or communication from one entity to another.
-
B.
hasRouteDirection
Indicates that a specified route is associated with a particular travel direction (e.g., inbound, outbound, northbound).
-
C.
hasRouteAlignment
Indicates that there is a defined spatial or geometric alignment associated with a route or pathway.
-
D.
hasRouteType
Indicates that there is a specific kind or category of route associated with an entity (e.g., road, rail, bus line).
-
E.
hasNotableRoute
Indicates that an entity (such as a transportation service or pathway) includes or is associated with a route that is considered significant, well-known, or otherwise noteworthy.
- 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_69a885ee6db8819099502bc5ce8af881 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa574094048190a2d7fc3ac904d51e |
completed | March 6, 2026, 4:25 a.m. |
| PD | Predicate disambiguation | batch_69a907b426dc8190975c024a50955368 |
completed | March 5, 2026, 4:33 a.m. |
| PDg | Predicate description generation | batch_69aa573ee8e0819084abf59f1ddbd1da |
completed | March 6, 2026, 4:25 a.m. |
Created at: March 4, 2026, 7:26 p.m.