Triple
T13455516
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IND/BMT Division |
E311220
|
entity |
| Predicate | hasTrainIdentification |
P109576
|
FINISHED |
| Object | lettered route designations |
—
|
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: lettered route designations | Statement: [IND/BMT Division, hasTrainIdentification, lettered route designations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrainIdentification Context triple: [IND/BMT Division, hasTrainIdentification, lettered route designations]
-
A.
usesTrainNumber
Indicates that one entity operates, identifies, or references another entity by a specific train number.
-
B.
hasRail
Indicates that something is equipped with, includes, or is connected to a rail or rail system.
-
C.
hasRailwayLineNumber
Indicates the specific identification number assigned to a railway line associated with an entity.
-
D.
hasTailTrain
Indicates that one entity possesses or is characterized by a tail-like train extending from it.
-
E.
trainTypeUsed
Indicates that a specific type or category of train is employed or operated in a given context or service.
- 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_69d806a938b8819097ec43a2229fc7f9 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaefc52448190b30d7999f44a9765 |
completed | April 12, 2026, 2:41 p.m. |
| PD | Predicate disambiguation | batch_69d9a03ce03481908c61094f0cc0c158 |
completed | April 11, 2026, 1:13 a.m. |
| PDg | Predicate description generation | batch_69dadce235f88190a6433395d2969811 |
completed | April 11, 2026, 11:44 p.m. |
Created at: April 9, 2026, 9:41 p.m.