Triple
T27542029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 客家话 |
E695260
|
entity |
| Predicate | 语法特征 |
P7162
|
FINISHED |
| Object | 趋向补语系统发达 |
—
|
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: 趋向补语系统发达 | Statement: [客家话, 语法特征, 趋向补语系统发达]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 语法特征 Context triple: [客家话, 语法特征, 趋向补语系统发达]
-
A.
linguisticFeature
Indicates a relationship where a linguistic property, pattern, or characteristic is attributed to or associated with a language-related entity (such as a word, phrase, or text).
-
B.
linguisticFeatureStatus
Indicates the current condition or state of a particular linguistic feature (such as whether it is present, active, obsolete, or otherwise characterized) in relation to an entity.
-
C.
hasLinguisticFeature
chosen
Indicates that an entity possesses a particular linguistic property, trait, or characteristic.
-
D.
formalismFeature
Indicates that something is a characteristic, component, or property that belongs to or defines a particular formal system or formalism.
-
E.
spanFeature
Indicates a relationship where a feature or characteristic extends across or covers a specified span or interval.
- 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_69ef5386c3e08190bfe33aa326e1f72b |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69f62f5ec8b481909241271f7d602dc9 |
completed | May 2, 2026, 5:07 p.m. |
| PD | Predicate disambiguation | batch_69f623ac3a9c8190a6ee0c137b09e4b0 |
completed | May 2, 2026, 4:17 p.m. |
Created at: April 27, 2026, 1:31 p.m.