Triple
T29033475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brussels–London high-speed rail corridor |
E737789
|
entity |
| Predicate | travelClassOffered |
P35839
|
FINISHED |
| Object | Standard |
—
|
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 | Statement: [Brussels–London high-speed rail corridor, travelClassOffered, Standard]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelClassOffered Context triple: [Brussels–London high-speed rail corridor, travelClassOffered, Standard]
-
A.
travelClassRelevance
Indicates the degree to which a particular travel class (e.g., economy, business) is pertinent or applicable within a given travel context or scenario.
-
B.
offersClassOfTravel
chosen
Indicates that a service provider makes a particular class or tier of travel (e.g., economy, business, first) available as an option.
-
C.
offersDomesticTravel
Indicates that one entity provides or makes available travel services within a single country to another entity.
-
D.
offersFirstClass
Indicates that one entity provides or makes available a first-class service, option, or accommodation to another entity.
-
E.
offersFootPassengerTravel
Indicates that an entity provides transportation services specifically for passengers traveling on foot, without vehicles.
- 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_69f077ef00fc81909325f084ad37c035 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f67d3624248190a36a9b2d2e9778d4 |
completed | May 2, 2026, 10:39 p.m. |
| PD | Predicate disambiguation | batch_69f678ce54b081908c26edfd49e39c60 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 28, 2026, 9:57 a.m.