Triple
T23129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oxford Road campus |
E459
|
entity |
| Predicate | languageOfInstitution |
P56
|
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: [Oxford Road campus, languageOfInstitution, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfInstitution Context triple: [Oxford Road campus, languageOfInstitution, English]
-
A.
primaryLanguageOfInstruction
chosen
Indicates the language that is mainly used as the medium of teaching or instruction for a given educational context.
-
B.
taughtAsForeignLanguageIn
Indicates that a language is taught as a foreign (non-native) language within a particular educational context or institution.
-
C.
typeOfInstitution
Indicates the specific kind or category of institution that an entity belongs to or is classified as.
-
D.
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.
-
E.
countryOfInstitution
Indicates the country in which an institution is located or officially based.
- 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_69a243b4ac2c8190b93c303df797b7b2 |
completed | Feb. 28, 2026, 1:24 a.m. |
| NER | Named-entity recognition | batch_69a246e94ca881908f7a7d2c0b293033 |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a246560af88190961ea00b35cf9388 |
completed | Feb. 28, 2026, 1:35 a.m. |
Created at: Feb. 28, 2026, 1:34 a.m.