Triple
T13299259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thai language |
E316763
|
entity |
| Predicate | usesSpacesBetweenWords |
P96266
|
FINISHED |
| Object | false |
—
|
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: false | Statement: [Thai language, usesSpacesBetweenWords, false]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesSpacesBetweenWords Context triple: [Thai language, usesSpacesBetweenWords, false]
-
A.
isWrittenWithSpace
Indicates that something is written or represented with spaces separating its components or elements.
-
B.
isWrittenWithoutSpace
chosen
Indicates that the referenced elements are written together as a single contiguous string, with no spaces between them.
-
C.
usesWord
Indicates that one entity employs, contains, or makes use of a particular word in its expression, content, or communication.
-
D.
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.
-
E.
isPlayOnWordsWith
Indicates a relationship where one expression is a pun or wordplay that depends on, echoes, or cleverly twists the wording or meaning of another expression.
- 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_69d806b40ab4819094adf6c374f4811a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f6893708190aeebf4c47386cff7 |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:28 p.m.