Triple
T34297891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carlton railway station |
E880083
|
entity |
| Predicate | hasPassengerStatisticsSource |
P200210
|
FINISHED |
| Object | Office of Rail and Road |
—
|
NE NERFINISHED |
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: Office of Rail and Road | Statement: [Carlton railway station, hasPassengerStatisticsSource, Office of Rail and Road]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPassengerStatisticsSource Context triple: [Carlton railway station, hasPassengerStatisticsSource, Office of Rail and Road]
-
A.
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.
-
B.
hasPassengerOperations
Indicates that an entity conducts or supports transportation services specifically for carrying passengers.
-
C.
hasPassengerUsageCategory
Indicates the classification of how a passenger-related resource or service is used (e.g., its usage type or category for passengers).
-
D.
hasPassengerTrafficFrom
Indicates that an entity receives or handles passenger traffic originating from another entity.
-
E.
hasThroughPassengersWith
Indicates that two transportation segments, services, or locations are connected by passengers who travel through them without starting or ending their journey there.
- F. None of above. chosen
Provenance (4 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_69f349b79f6c81909cb468c92c39c74d |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff7ae5d088819089aa3b6360b6b749 |
completed | May 9, 2026, 6:20 p.m. |
| PD | Predicate disambiguation | batch_69ff7a4df6488190bf60d675b36b1d6d |
completed | May 9, 2026, 6:17 p.m. |
| PDg | Predicate description generation | batch_69ff7ae4bc948190a4cd21a60d091977 |
completed | May 9, 2026, 6:20 p.m. |
Created at: May 1, 2026, 1:57 a.m.