Triple
T4178947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MBTA diesel locomotives |
E86545
|
entity |
| Predicate | fleetIncludesRebuiltUnits |
P54249
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [MBTA diesel locomotives, fleetIncludesRebuiltUnits, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fleetIncludesRebuiltUnits Context triple: [MBTA diesel locomotives, fleetIncludesRebuiltUnits, yes]
-
A.
fleetIncludes
Indicates that a particular fleet contains or is composed of the specified entity or entities as its members.
-
B.
fleetSize
Indicates the total number of vehicles, vessels, or units that collectively make up a fleet associated with an entity.
-
C.
fleetBase
Indicates that one entity serves as the primary homeport, headquarters, or main operating base for a fleet associated with the other entity.
-
D.
fleetCommander
Indicates that one entity serves as the commanding officer or overall leader in charge of the operations and decisions of a fleet associated with another entity.
-
E.
otherShipsInFleet
Indicates that the subject ship and the object ship are distinct members of the same fleet.
- 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_69aed93de98c8190ad838ce507b77c8a |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af07078cb081909f64326b12522410 |
completed | March 9, 2026, 5:44 p.m. |
| PD | Predicate disambiguation | batch_69af019155448190b19868583272513f |
completed | March 9, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69af07059d288190a1ea79449414fbce |
completed | March 9, 2026, 5:44 p.m. |
Created at: March 9, 2026, 3:45 p.m.