Triple
T9077639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arlington Cemetery station |
E217527
|
entity |
| Predicate | weekdayRidershipLevel |
P17463
|
FINISHED |
| Object | lower than average Washington Metro station due to tourist-oriented demand |
—
|
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: lower than average Washington Metro station due to tourist-oriented demand | Statement: [Arlington Cemetery station, weekdayRidershipLevel, lower than average Washington Metro station due to tourist-oriented demand]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: weekdayRidershipLevel Context triple: [Arlington Cemetery station, weekdayRidershipLevel, lower than average Washington Metro station due to tourist-oriented demand]
-
A.
dailyRidershipCategory
chosen
Indicates the classification of an entity based on the typical number of riders it serves per day.
-
B.
dailyRidershipPeak
Indicates that the relationship specifies the highest number of riders or users recorded for a service or system within a single day.
-
C.
dailyRidership
Indicates the typical number of people who use or ride a given transportation service each day.
-
D.
weekdayPeakDirectionService
Indicates that the service operates primarily during weekday peak travel periods in a specific direction.
-
E.
annualRidership
Indicates the total number of passengers who use a transportation service over the course of one year.
- 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_69ca83d6c14c8190bc056d927f00a2a2 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc95c7d3688190a4c1c6a92965eae4 |
completed | April 1, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69cc65fa79bc81908b46f05c8bba920f |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:12 p.m.