Triple
T28408133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UC |
E719592
|
entity |
| Predicate | commonAbbreviationFor |
P32259
|
FINISHED |
| Object | University College, University of Toronto |
—
|
NE NERFINISHED |
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: University College, University of Toronto | Statement: [UC, commonAbbreviationFor, University College, University of Toronto]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonAbbreviationFor Context triple: [UC, commonAbbreviationFor, University College, University of Toronto]
-
A.
commonAbbreviationLanguage
Indicates that one language is commonly abbreviated or represented by another language or code in written or symbolic form.
-
B.
isCommonAbbreviation
chosen
Indicates that one term is a widely used shortened or abbreviated form of another term.
-
C.
alternativeAbbreviation
Indicates that one term serves as an alternative shortened form or acronym for another term.
-
D.
abreviaturaFrecuente
Indicates that one term is a common or frequently used abbreviation of another term.
-
E.
abbreviationOrShortForm
Indicates that one term is an abbreviation or shortened form of another term.
- 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_69eff6f0f37c8190b37bc6fab08a9449 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f7cec454a88190a9f3bbee2b856636 |
completed | May 3, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69f7c8977c288190997a892ec5f756ed |
completed | May 3, 2026, 10:13 p.m. |
Created at: April 28, 2026, 1:25 a.m.