Triple
T1273359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | British Rail |
E15757
|
entity |
| Predicate | standardTicketingSystem |
P25925
|
FINISHED |
| Object | BR computerised reservation system |
—
|
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: BR computerised reservation system | Statement: [British Rail, standardTicketingSystem, BR computerised reservation system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: standardTicketingSystem Context triple: [British Rail, standardTicketingSystem, BR computerised reservation system]
-
A.
ticketSystem
chosen
Indicates a relationship where an entity is managed, tracked, or processed through a ticket-based system for handling requests, issues, or tasks.
-
B.
standardIssueFor
Indicates that something is the typical or officially designated item or version provided for use in a particular context, role, or organization.
-
C.
issueType
Indicates the specific category or classification assigned to an issue within a tracking or management context.
-
D.
typeOfSupport
Indicates the kind or category of assistance, help, or backing provided in a given context.
-
E.
standardType
Indicates that one entity is classified as the standard, canonical, or reference type for another entity or context.
- 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_69a4935a94308190bb92555b79032824 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4c31602b8819087a57e8d390cae7a |
completed | March 1, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69a4bee0be808190a8ccac6a41851fdd |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:50 p.m.