Triple
T21620598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ivey Asia campus, Hong Kong |
E533565
|
entity |
| Predicate | usesCaseMethod |
P33646
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Ivey Asia campus, Hong Kong, usesCaseMethod, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesCaseMethod Context triple: [Ivey Asia campus, Hong Kong, usesCaseMethod, true]
-
A.
usesCaseSystem
Indicates that one entity employs or operates using a particular case system (e.g., grammatical or structural case-marking system).
-
B.
usesCaseHarmony
Indicates that one element selects or governs another element such that their grammatical cases are compatible or harmonized according to the language’s case system.
-
C.
usedInCase
Indicates that something (such as an item, method, or piece of information) is employed or applied within a particular case or instance.
-
D.
usesMethods
chosen
Indicates that one entity employs, applies, or relies on specific methods or techniques to perform an action or achieve a result.
-
E.
usesClass
Indicates that one entity makes use of, depends on, or is implemented using a particular class in its structure or behavior.
- 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_69e0c464fba881908d0ff2ac80511ce1 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef3baeeae48190b78583b3bec8ee33 |
completed | April 27, 2026, 10:34 a.m. |
| PD | Predicate disambiguation | batch_69e69665fe8c8190af7e38785db188b2 |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:34 p.m.