Triple
T13299262
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thai language |
E316763
|
entity |
| Predicate | politeParticleMale |
P17541
|
FINISHED |
| Object | ครับ |
—
|
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: ครับ | Statement: [Thai language, politeParticleMale, ครับ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: politeParticleMale Context triple: [Thai language, politeParticleMale, ครับ]
-
A.
honorificParticle
chosen
Indicates that a grammatical particle is used to convey respect, politeness, or social status toward a referent in the expression.
-
B.
hasPolitePronoun
Indicates that one entity refers to another using a polite or honorific form of address in language.
-
C.
honorificGender
Indicates that a particular honorific or title is associated with a specific gender or gendered form.
-
D.
politenessLevel
Indicates the degree of courteousness or respectfulness expressed by one entity toward another in an interaction.
-
E.
honorificPrefix
Indicates the formal title or respectful prefix (e.g., "Dr.", "Mr.", "Prof.") used before a person's name to denote status, role, or honor.
- 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.