Triple
T13918889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xibe script |
E334689
|
entity |
| Predicate | hasSpacesBetweenWords |
P36966
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Xibe script, hasSpacesBetweenWords, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpacesBetweenWords Context triple: [Xibe script, hasSpacesBetweenWords, yes]
-
A.
isWrittenWithSpace
chosen
Indicates that something is written or represented with spaces separating its components or elements.
-
B.
isWrittenWithoutSpace
Indicates that the referenced elements are written together as a single contiguous string, with no spaces between them.
-
C.
hasAlternativeSpacing
Indicates that an entity is associated with one or more alternative ways of spacing its characters or components compared to a primary or standard form.
-
D.
hasFourWords
Indicates that the related item (such as a phrase, title, or name) consists of exactly four words.
-
E.
hasBasicWordOrder
Indicates the typical sequence in which core sentence elements (such as subject, verb, and object) are ordered in a language.
- 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_69d81c5f739081908bc05b2461f54828 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de272753e48190bc609482635280ff |
completed | April 14, 2026, 11:38 a.m. |
| PD | Predicate disambiguation | batch_69de059e4ba881908554f72e889719fa |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:16 p.m.