Triple
T17287407
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MPI MP36PH-3C |
E419693
|
entity |
| Predicate | MBTAUsageType |
P109578
|
FINISHED |
| Object | leased or borrowed units |
—
|
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: leased or borrowed units | Statement: [MPI MP36PH-3C, MBTAUsageType, leased or borrowed units]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: MBTAUsageType Context triple: [MPI MP36PH-3C, MBTAUsageType, leased or borrowed units]
-
A.
commuterRailMode
Indicates that the relationship involves travel or transportation specifically by commuter rail as the mode of transit between the related entities.
-
B.
hasPublicTransportUsage
Indicates that an entity makes use of, or is associated with the use of, public transportation services.
-
C.
dailyRidershipCategory
Indicates the classification of an entity based on the typical number of riders it serves per day.
-
D.
passesUsedForTransportation
Indicates that the passes are utilized as a means or instrument for transporting people or goods.
-
E.
usedByTransitSystem
chosen
Indicates that something is utilized or operated by a transit or public transportation 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_69d886db32608190a61e18862c5a8af6 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e43780fad88190b82193c8335e2f11 |
completed | April 19, 2026, 2:01 a.m. |
| PD | Predicate disambiguation | batch_69e3b0118ad08190b119cd219c68ba67 |
completed | April 18, 2026, 4:23 p.m. |
Created at: April 10, 2026, 5:40 a.m.