Triple
T2102475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | West Midlands Railway |
E37119
|
entity |
| Predicate | offersClassOfTravel |
P35839
|
FINISHED |
| Object | standard class |
—
|
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: standard class | Statement: [West Midlands Railway, offersClassOfTravel, standard class]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersClassOfTravel Context triple: [West Midlands Railway, offersClassOfTravel, standard class]
-
A.
offersTours
Indicates that one entity provides or makes available guided tours or tour services to another entity.
-
B.
travelsOn
Indicates that an entity moves or journeys using a particular route, path, or mode of transportation.
-
C.
voyageType
Indicates the specific category or nature of a journey or trip that an entity undertakes.
-
D.
fareProduct
Indicates a relationship where a specific fare or price offering is associated with a particular product or service option.
-
E.
hasTypeOfFlights
Indicates that an entity offers, includes, or is associated with specific categories or kinds of flights.
- 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_69a8861828948190924aa30c08806b3a |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abbabe1e9081908ea66c5406e2f1d9 |
completed | March 7, 2026, 5:42 a.m. |
| PD | Predicate disambiguation | batch_69abb7b7b6288190afa11b4d93bd5666 |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb9ce3ff08190a9501f8bb821c01c |
completed | March 7, 2026, 5:38 a.m. |
Created at: March 4, 2026, 7:43 p.m.