Triple
T1371982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eastern Counties Railway |
E30131
|
entity |
| Predicate | passengerService |
P18240
|
FINISHED |
| Object | operated passenger trains |
—
|
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: operated passenger trains | Statement: [Eastern Counties Railway, passengerService, operated passenger trains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: passengerService Context triple: [Eastern Counties Railway, passengerService, operated passenger trains]
-
A.
formerPassengerService
Indicates that an entity previously provided passenger transportation services but no longer does so.
-
B.
hasPassengerServicesTo
Indicates that a transportation provider operates passenger services connecting one location or entity to another.
-
C.
passengers
Indicates that one entity is traveling in or being transported by another entity, typically as a non-operating occupant.
-
D.
passengerConfiguration
Indicates how passengers are arranged, seated, or distributed within a vehicle or transport setting.
-
E.
hasPassengerHandling
chosen
Indicates that an entity is responsible for or involved in managing the processes and services related to handling passengers.
- 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_69a498f912008190a376a98b207b2071 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c2f314c081909c0ab80397d96abb |
completed | March 1, 2026, 10:51 p.m. |
| PD | Predicate disambiguation | batch_69a4befb08b88190be966fa1aadd4bcd |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:57 p.m.