Triple
T9745980
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harajuku Station |
E236307
|
entity |
| Predicate | hasDailyPassengerUsage |
P30663
|
FINISHED |
| Object | hundreds of thousands (approximate) |
—
|
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: hundreds of thousands (approximate) | Statement: [Harajuku Station, hasDailyPassengerUsage, hundreds of thousands (approximate)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDailyPassengerUsage Context triple: [Harajuku Station, hasDailyPassengerUsage, hundreds of thousands (approximate)]
-
A.
hasDailyPassengerTraffic
chosen
Indicates the number of passengers that regularly use or pass through something (such as a station or route) each day.
-
B.
hasPassengerUsageStatistics
Indicates the relationship by which an entity is associated with data describing how passengers use it, such as counts, frequencies, or patterns of passenger activity.
-
C.
hasPublicTransportUsage
Indicates that an entity makes use of, or is associated with the use of, public transportation services.
-
D.
hasPassengerUsageCategory
Indicates the classification of how a passenger-related resource or service is used (e.g., its usage type or category for passengers).
-
E.
hasDailyUse
Indicates that something is used or occurs on a daily, regular basis.
- 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_69ca84d3e24481908a476e2231123cf9 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9f65ad788190b68d731b6f516d93 |
completed | April 1, 2026, 10:42 p.m. |
| PD | Predicate disambiguation | batch_69cd03cc128c81908b84ef224f858b4e |
completed | April 1, 2026, 11:38 a.m. |
Created at: March 30, 2026, 8:23 p.m.