Triple
T3491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MBTA Fitchburg Line |
E65
|
entity |
| Predicate | fareSystem |
P395
|
FINISHED |
| Object | MBTA zone-based commuter rail fares |
—
|
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 zone-based commuter rail fares | Statement: [MBTA Fitchburg Line, fareSystem, MBTA zone-based commuter rail fares]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fareSystem Context triple: [MBTA Fitchburg Line, fareSystem, MBTA zone-based commuter rail fares]
-
A.
FIPSCode
Indicates the standardized Federal Information Processing Standards (FIPS) code assigned to identify a specific geographic or administrative entity.
-
B.
transportation
Indicates the movement of someone or something from one place to another, typically using a vehicle or transit system.
-
C.
operatesBy
Indicates that an entity performs its function, action, or process through the use or application of another entity (e.g., a method, mechanism, or principle).
-
D.
drivesOn
Indicates that an entity uses or travels along a particular route, surface, or roadway as its path of movement.
-
E.
drivingSide
Indicates which side of the road (left or right) vehicles are required to drive on in a given jurisdiction.
- 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_69a238d6b47881909e68288aed2fd858 |
completed | Feb. 28, 2026, 12:37 a.m. |
| NER | Named-entity recognition | batch_69a23bcc8eb48190b897cc331563980a |
completed | Feb. 28, 2026, 12:50 a.m. |
| PD | Predicate disambiguation | batch_69a23994309081909ff3e869deef2156 |
completed | Feb. 28, 2026, 12:40 a.m. |
| PDg | Predicate description generation | batch_69a23bcb4bbc819093775f623998d62d |
completed | Feb. 28, 2026, 12:50 a.m. |
Created at: Feb. 28, 2026, 12:40 a.m.