Triple
T31275178
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | กระทรวงกลาโหม |
E797496
|
entity |
| Predicate | ใช้ภาษา |
P18209
|
FINISHED |
| Object | ภาษาไทย |
—
|
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: ภาษาไทย | Statement: [กระทรวงกลาโหม, ใช้ภาษา, ภาษาไทย]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ใช้ภาษา Context triple: [กระทรวงกลาโหม, ใช้ภาษา, ภาษาไทย]
-
A.
languageUse
chosen
Indicates the language or languages an entity uses for communication, expression, or interaction.
-
B.
usesLanguageFor
Indicates that an entity employs a particular language as a tool or medium to perform some activity, function, or purpose.
-
C.
linguisticUsage
Indicates how a linguistic form, expression, or construction is used in language, such as its typical context, function, or register.
-
D.
usedInLanguage
Indicates that something (such as a word, expression, or symbol) is employed or occurs within a particular language.
-
E.
typicalLanguageUse
Indicates that one entity is the language most commonly or habitually used by another entity in ordinary communication or contexts.
- 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_69f224de2bbc819081af6c32e1d857b9 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69edbb7648190bd89c57e0932eac1 |
completed | May 3, 2026, 1:03 a.m. |
| PD | Predicate disambiguation | batch_69f69d1bf8cc8190a78dfa5ab00daf3a |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 29, 2026, 9:13 p.m.