Triple
T36304492
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zhuang script |
E893906
|
entity |
| Predicate | belongsToWritingSystemFamily |
P201224
|
FINISHED |
| Object | Latin writing systems |
—
|
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: Latin writing systems | Statement: [Zhuang script, belongsToWritingSystemFamily, Latin writing systems]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToWritingSystemFamily Context triple: [Zhuang script, belongsToWritingSystemFamily, Latin writing systems]
-
A.
belongsToRomanizationFamily
Indicates that one romanization system is a member of, or classified under, a broader family or group of related romanization systems.
-
B.
writingSystemFamilyRole
Indicates the role or function that a writing system family plays within a broader linguistic, cultural, or communicative context.
-
C.
haveWritingSystemsForSomeMembers
Indicates that at least some members of a group or category possess or use one or more writing systems.
-
D.
hasCommonWritingSystem
Indicates that two entities use the same or mutually intelligible writing system for written communication.
-
E.
appliesToWritingSystem
Indicates that something is relevant or specifically pertains to a particular writing system.
- 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_69f76e4c1b248190b10667d0213537fe |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ffdf47d9608190830ca23d9cef6409 |
completed | May 10, 2026, 1:28 a.m. |
| PD | Predicate disambiguation | batch_69ffdf00e2b4819082dd5cb78f316baf |
completed | May 10, 2026, 1:27 a.m. |
| PDg | Predicate description generation | batch_69ffdf46e18c8190a5e4f4e5211cb087 |
completed | May 10, 2026, 1:28 a.m. |
Created at: May 3, 2026, 4:09 p.m.