Triple
T1504486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University College London |
E33866
|
entity |
| Predicate | acceptsInternationalStudents |
P16422
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [University College London, acceptsInternationalStudents, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: acceptsInternationalStudents Context triple: [University College London, acceptsInternationalStudents, yes]
-
A.
hasInternationalStudents
chosen
Indicates that an institution or organization includes students who come from countries other than the one in which it is located.
-
B.
acceptsStudents
Indicates that an institution or program allows and takes in students as participants or members.
-
C.
internationalStudentsShare
Indicates the proportion or percentage of a population or group that consists of international students.
-
D.
offersInternationalPrograms
Indicates that an institution or organization provides programs or courses available to participants from other countries or across national borders.
-
E.
isInternational
Indicates that something has a connection to, involves, or extends across more than one country.
- 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_69a885f352a4819099b24ff15489dede |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90584b8b881908e112c7e59163812 |
completed | March 5, 2026, 4:24 a.m. |
| PD | Predicate disambiguation | batch_69a88727ce48819089b482cdc25453d1 |
completed | March 4, 2026, 7:25 p.m. |
Created at: March 4, 2026, 7:24 p.m.