Triple
T21691198
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Medinah station |
E535371
|
entity |
| Predicate | servedByOperatorType |
P21524
|
FINISHED |
| Object | commuter rail operator |
—
|
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: commuter rail operator | Statement: [Medinah station, servedByOperatorType, commuter rail operator]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servedByOperatorType Context triple: [Medinah station, servedByOperatorType, commuter rail operator]
-
A.
typicalOperatorService
Indicates that an entity commonly performs or provides a particular operational service in a standard or expected manner.
-
B.
typicalOperatorType
chosen
Indicates the usual or most common type or category of operator associated with a given entity or context.
-
C.
usedByOperator
Indicates that something is utilized or operated by a particular operator or operating entity.
-
D.
agencyTypeOfOperator
Indicates the specific type or category of agency to which the operator belongs or by which the operator is characterized.
-
E.
typicalOperator
Indicates that an entity commonly or normally performs operations on, or acts upon, another entity in a standard or expected manner.
- 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_69e0c46a6ee481908836e1420fb78c9b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef96cfaab08190b400e1538afc8c43 |
completed | April 27, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69e6969113cc8190ab69855ef5667e4b |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:45 p.m.