Triple
T4044063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monument Metro station |
E84020
|
entity |
| Predicate | isOneOfBusiestOnSystem |
P15948
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Monument Metro station, isOneOfBusiestOnSystem, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isOneOfBusiestOnSystem Context triple: [Monument Metro station, isOneOfBusiestOnSystem, true]
-
A.
isBusiestInSystem
Indicates that an entity has the highest level of activity or load compared to all other entities within the same system.
-
B.
isBusiestStationIn
Indicates that a station has the highest level of activity (e.g., passenger or traffic volume) within a specified area or system.
-
C.
isOneOfBusiestStopsOn
chosen
Indicates that a stop ranks among the most heavily used or frequently served stops on a given route or line.
-
D.
isMostPopularRouteOn
Indicates that a particular route is the most frequently chosen or favored option on a given transportation line, network, or service.
-
E.
hasHeavyPassengerTraffic
Indicates that an entity experiences a high volume of passenger movement or usage over a given period.
- 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_69aed930bd5c819083e7dcc14fc44f69 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb5d759c8190b61fbbe94ffe2bf7 |
completed | March 9, 2026, 4:54 p.m. |
| PD | Predicate disambiguation | batch_69aef900386481909d04555a9ec9b0e3 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:37 p.m.