Triple
T35905479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daic languages |
E1038459
|
entity |
| Predicate | includesOfficialLanguageOf |
P112296
|
FINISHED |
| Object | Thailand |
E5032
|
NE 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: Thailand | Statement: [Daic languages, includesOfficialLanguageOf, Thailand]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesOfficialLanguageOf Context triple: [Daic languages, includesOfficialLanguageOf, Thailand]
-
A.
usesOfficialLanguageOf
Indicates that one entity adopts and employs the official language of another entity for communication or formal purposes.
-
B.
hasLanguageOfficial
chosen
Indicates that a language holds official status within a given entity, such as a country, region, or organization.
-
C.
hasOfficialCountryLanguage
Indicates that a country recognizes a particular language as one of its official languages for governmental or legal purposes.
-
D.
hasOfficialLanguageOfLocation
Indicates that a location has a specified language recognized as its official language.
-
E.
shareOfficialLanguage
Indicates that two entities have at least one official language in common.
- F. None of above.
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_69f76e2259608190bf6788a132e0d139 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037ce70f54819082946dad8d380825 |
completed | May 12, 2026, 7:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a38bfc8e2bc8190b02ea3af1ca68d76 |
completed | June 22, 2026, 4:53 a.m. |
| PD | Predicate disambiguation | batch_6a037a069e6c8190857b611fffb7b867 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:07 p.m.