Triple
T1631237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MBTA Type 8 Light Rail Vehicle |
E35259
|
entity |
| Predicate | usedOnRouteType |
P13326
|
FINISHED |
| Object | surface light rail routes |
—
|
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: surface light rail routes | Statement: [MBTA Type 8 Light Rail Vehicle, usedOnRouteType, surface light rail routes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedOnRouteType Context triple: [MBTA Type 8 Light Rail Vehicle, usedOnRouteType, surface light rail routes]
-
A.
hasRouteType
chosen
Indicates that there is a specific kind or category of route associated with an entity (e.g., road, rail, bus line).
-
B.
includesRouteType
Indicates that one entity’s set of routes contains or covers a specific type or category of route associated with another entity.
-
C.
operatedOnRoute
Indicates that a transportation service or vehicle was active and provided service along a specified route.
-
D.
isPartOfRoute
Indicates that something (such as a segment, stop, or step) belongs to and is contained within a larger route.
-
E.
notableRouteType
Indicates that a route is particularly significant or well-known for a specific type or category (e.g., scenic, historic, commercial).
- 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_69a886036bc081909ff5de16dbe5e8ea |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a9431af5ac8190893133f1ae490142 |
completed | March 5, 2026, 8:47 a.m. |
| PD | Predicate disambiguation | batch_69a907c91c888190b6ed295c1a2e0977 |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:28 p.m.