Triple
T4759899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zeta |
E105673
|
entity |
| Predicate | belongsToWritingSystemType |
P9330
|
FINISHED |
| Object | Segmental alphabet |
—
|
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: Segmental alphabet | Statement: [Zeta, belongsToWritingSystemType, Segmental alphabet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToWritingSystemType Context triple: [Zeta, belongsToWritingSystemType, Segmental alphabet]
-
A.
writingSystemClass
chosen
Indicates that one entity is classified as a type or category of writing system to which the other entity belongs.
-
B.
writingSystem
Indicates that one entity is the script or system of written symbols used to represent the language or content of another entity.
-
C.
writingSystemUsedIn
Indicates that a particular writing system is employed for written communication within a given language, region, or context.
-
D.
hasWritingSystemForMajorLanguage
Indicates that there exists a writing system used to represent a major language associated with the given entity.
-
E.
writingSystemFound
Indicates that a particular writing system is present, attested, or used in association with a given entity (such as a language, region, or community).
- 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_69bd43f14cac819081c7c69803648211 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd650dc7fc81909b483ef3c456ae0d |
completed | March 20, 2026, 3:17 p.m. |
| PD | Predicate disambiguation | batch_69bd6225c9488190afee5bb3619d0365 |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:20 p.m.