Triple
T19768506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gangnam Station |
E474819
|
entity |
| Predicate | hasHighPassengerVolume |
P35231
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Gangnam Station, hasHighPassengerVolume, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHighPassengerVolume Context triple: [Gangnam Station, hasHighPassengerVolume, yes]
-
A.
hasHeavyPassengerTraffic
chosen
Indicates that an entity experiences a high volume of passenger movement or usage over a given period.
-
B.
hasLargeVolume
Indicates that an entity possesses or is characterized by a comparatively large physical or quantitative volume.
-
C.
hasPassengerArea
Indicates that an object or vehicle includes a designated area intended for carrying passengers.
-
D.
hasCrewCapacity
Indicates that an entity is capable of accommodating a specified number of crew members.
-
E.
hasCrowdLevel
Indicates the degree or intensity of how crowded a place, event, or situation is.
- 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_69d8e51a43a08190956bc6df13c91a77 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65359bb9881908f48282b63a83f2f |
completed | April 20, 2026, 4:24 p.m. |
| PD | Predicate disambiguation | batch_69e5305016e08190b9561a96baecb0b8 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:48 p.m.