Triple
T5702096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ann Arbor Railroad (original) |
E125687
|
entity |
| Predicate | operatedCarFerries |
P5933
|
FINISHED |
| Object | rail car ferries on Lake Michigan |
—
|
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: rail car ferries on Lake Michigan | Statement: [Ann Arbor Railroad (original), operatedCarFerries, rail car ferries on Lake Michigan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatedCarFerries Context triple: [Ann Arbor Railroad (original), operatedCarFerries, rail car ferries on Lake Michigan]
-
A.
ferryOperator
chosen
Indicates that one entity operates, manages, or runs a ferry service for another entity or in a particular context.
-
B.
hasFerryService
Indicates that there is an operational ferry connection or transport service available between the related locations or entities.
-
C.
hasFerryType
Indicates that an entity (such as a ferry route or service) is associated with a specific type or category of ferry.
-
D.
transportOperator
Indicates that an entity is responsible for operating or managing the transportation of people or goods between locations.
-
E.
ferryRange
Indicates the maximum distance an aircraft can fly without payload or passengers, typically with full fuel, under specified conditions.
- 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_69c0082c96988190b3a6a201edce472a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0245581988190a819b8137533ed31 |
completed | March 22, 2026, 5:18 p.m. |
| PD | Predicate disambiguation | batch_69c021c2d8bc8190b947c7d1f423d2f3 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:45 p.m.