Triple
T24193966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North–South Wales rail corridor |
E599777
|
entity |
| Predicate | languageOfOfficialContext |
P6898
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [North–South Wales rail corridor, languageOfOfficialContext, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfOfficialContext Context triple: [North–South Wales rail corridor, languageOfOfficialContext, English]
-
A.
officialLanguage
Indicates that a particular language has been formally designated by an authority as the official language used for government, legal, or administrative purposes in a given jurisdiction.
-
B.
languageOfOfficialAnnouncements
chosen
Indicates the language used for formal or official public announcements issued by an authority.
-
C.
previousOfficialLanguage
Indicates that one language formerly held official status in a country, region, or organization before being replaced or losing that status.
-
D.
languageOfOfficialReports
Indicates the language in which an entity’s official reports are written or issued.
-
E.
shareOfficialLanguage
Indicates that two entities have at least one official language in common.
- 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_69e288cdc8b88190bf2f835d3cb4ca28 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1e24947948190b609a39a2b8828ad |
completed | April 29, 2026, 10:49 a.m. |
| PD | Predicate disambiguation | batch_69f1c43e55688190b55fc20274ed471c |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 17, 2026, 11:36 p.m.