Triple
T7002370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King of Siam |
E162365
|
entity |
| Predicate | associatedLanguagePolicy |
P187
|
FINISHED |
| Object | promotion of Thai language |
—
|
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: promotion of Thai language | Statement: [King of Siam, associatedLanguagePolicy, promotion of Thai language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedLanguagePolicy Context triple: [King of Siam, associatedLanguagePolicy, promotion of Thai language]
-
A.
languagePolicyIssue
Indicates that there is a problem, conflict, or concern related to rules or practices governing language use.
-
B.
languagePolicyRegion
Indicates that a particular language policy applies within, or is associated with, a specific geographic or administrative region.
-
C.
languageOfRegistrationPolicies
Indicates the language in which the registration policies are written or officially specified.
-
D.
eligibleLanguage
Indicates that a particular language satisfies the required conditions to be considered valid or allowed in a given context.
-
E.
hasOfficialLanguagePolicy
chosen
Indicates that there exists a formally adopted rule or set of rules governing the use, status, or regulation of one or more languages within a given context or jurisdiction.
- 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_69c68857ffc08190857dc62cd5253777 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dc1115c48190a9363473ae21b6c1 |
completed | March 27, 2026, 7:35 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c67c94819084fdcf0398606027 |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:33 p.m.