Triple
T3015349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wu Chinese |
E82322
|
entity |
| Predicate | hasScriptUsage |
P45018
|
FINISHED |
| Object | primarily written with Standard Chinese grammar and vocabulary |
—
|
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: primarily written with Standard Chinese grammar and vocabulary | Statement: [Wu Chinese, hasScriptUsage, primarily written with Standard Chinese grammar and vocabulary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasScriptUsage Context triple: [Wu Chinese, hasScriptUsage, primarily written with Standard Chinese grammar and vocabulary]
-
A.
containsScript
Indicates that one entity includes or embeds the script of another entity within it.
-
B.
hasScriptStatus
Indicates that an entity has a particular script-related state or condition, such as whether a script is present, active, or in a given status.
-
C.
usesScriptDerivedFrom
Indicates that one entity employs a writing system that is historically or structurally derived from the script used by another entity.
-
D.
hasUsageNote
Indicates that there is an associated explanatory note describing how or when something should be used.
-
E.
hasScriptHistory
Indicates that an entity is associated with a record or chronology of scripts or writing systems it has used or been represented in over time.
- F. None of above. chosen
Provenance (4 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_69ad8b1eb53481908c39bbcd1ec104b2 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9a6b37288190a6965d183ca4b08b |
completed | March 8, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69ad961a97188190809dc73430a8eda8 |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad97ba55dc8190b6dddddfb751cf64 |
completed | March 8, 2026, 3:37 p.m. |
Created at: March 8, 2026, 3 p.m.