Triple
T19717692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 香港中文大学工程学院创院院长 |
E473521
|
entity |
| Predicate | 任职机构类型 |
P102976
|
FINISHED |
| Object | 公立研究型大学 |
—
|
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: 公立研究型大学 | Statement: [香港中文大学工程学院创院院长, 任职机构类型, 公立研究型大学]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 任职机构类型 Context triple: [香港中文大学工程学院创院院长, 任职机构类型, 公立研究型大学]
-
A.
employerType
Indicates the classification or category of an employer in relation to the entity (e.g., public, private, nonprofit, self-employed).
-
B.
办学性质
chosen
Indicates the nature or type of an educational institution’s operation (e.g., public, private, or other organizing/operating character).
-
C.
employmentType
Indicates the specific kind or category of employment relationship that exists between an individual and an employer (e.g., full-time, part-time, contract).
-
D.
organizationType
Indicates the specific category or classification of an organization in terms of its nature, structure, or primary function.
-
E.
institutionTypeOfOrganizer
Indicates the type or category of institution to which the organizer of an event or activity belongs.
- 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_69d8e516dd048190a0b6c93ea3e71f58 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6440ec9e881909b75c0ebefab827f |
completed | April 20, 2026, 3:19 p.m. |
| PD | Predicate disambiguation | batch_69e530438c60819082364c7be3eef6f0 |
completed | April 19, 2026, 7:42 p.m. |
Created at: April 10, 2026, 1:46 p.m.