Triple
T6154445
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | bengoshi |
E137283
|
entity |
| Predicate | writesSystem |
P69491
|
FINISHED |
| Object | Japanese writing system |
—
|
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: Japanese writing system | Statement: [bengoshi, writesSystem, Japanese writing system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: writesSystem Context triple: [bengoshi, writesSystem, Japanese writing system]
-
A.
writesTo
Indicates that one entity produces and records information, data, or content into another entity as a destination or storage target.
-
B.
writingSystemStatus
Indicates the current functional or sociolinguistic state of a writing system, such as whether it is actively used, obsolete, official, or endangered.
-
C.
writingSystemScope
Indicates the range or extent of content, languages, or contexts to which a particular writing system applies or is used.
-
D.
writtenTo
Indicates that something has been addressed or directed in written form to a particular recipient.
-
E.
writingSystem
Indicates that one entity is the script or system of written symbols used to represent the language or content of another entity.
- 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_69c008a45d008190832a9e19f5d63406 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05d01ddb0819085b5f5338b86a25d |
completed | March 22, 2026, 9:20 p.m. |
| PD | Predicate disambiguation | batch_69c055f39e0881909ae56444b1b48929 |
completed | March 22, 2026, 8:49 p.m. |
| PDg | Predicate description generation | batch_69c056c87340819088003f427706ebf8 |
completed | March 22, 2026, 8:53 p.m. |
Created at: March 22, 2026, 4:17 p.m.