Triple
T1893151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BAL |
E41917
|
entity |
| Predicate | usedInTimetables |
P21407
|
FINISHED |
| Object | Amtrak timetables |
—
|
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: Amtrak timetables | Statement: [BAL, usedInTimetables, Amtrak timetables]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInTimetables Context triple: [BAL, usedInTimetables, Amtrak timetables]
-
A.
isUsedInTransportTimetables
chosen
Indicates that something is employed or referenced within transport timetables or schedules.
-
B.
usedForRailwayTimetables
Indicates that something is employed in the creation, organization, or presentation of railway timetables.
-
C.
railwayTimeUsage
Indicates how much time is spent using or operating a railway within a given context or period.
-
D.
areUsedIn
Indicates that certain entities serve as components, tools, or resources within a particular process, context, or application.
-
E.
usedInPartOf
Indicates that something is utilized or plays a functional role within a specific component or subpart of a larger whole.
- 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_69a8864b6de0819098d089f6a1b910a7 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb1480a6c81909fcf5cce4c42fed4 |
completed | March 7, 2026, 5:02 a.m. |
| PD | Predicate disambiguation | batch_69abafe7e7e88190b58c0df59187c0c2 |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:34 p.m.