Triple
T5829876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elephant & Castle Underground station |
E129317
|
entity |
| Predicate | hasAnnualUsageCategory |
P8370
|
FINISHED |
| Object | high passenger usage |
—
|
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: high passenger usage | Statement: [Elephant & Castle Underground station, hasAnnualUsageCategory, high passenger usage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAnnualUsageCategory Context triple: [Elephant & Castle Underground station, hasAnnualUsageCategory, high passenger usage]
-
A.
isUsedAllYear
Indicates that something is utilized or remains in active use throughout the entire year, without being limited to a particular season or period.
-
B.
isAnnual
Indicates that something occurs, is scheduled, or is valid once every year.
-
C.
hasPassengerUsageCategory
chosen
Indicates the classification of how a passenger-related resource or service is used (e.g., its usage type or category for passengers).
-
D.
hasAnnualList
Indicates that an entity maintains or is associated with a list that is updated or issued on an annual basis.
-
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_69c00849d55481908b4f9f5543e0bf6d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c044ab0a048190b84be40fb13c0f50 |
completed | March 22, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69c03341e5888190a5f219b6f92cb161 |
completed | March 22, 2026, 6:21 p.m. |
Created at: March 22, 2026, 3:54 p.m.