Triple
T774067
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Songkran |
E16347
|
entity |
| Predicate | hasTraditionalDress |
P3114
|
FINISHED |
| Object | colorful floral shirts |
—
|
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: colorful floral shirts | Statement: [Songkran, hasTraditionalDress, colorful floral shirts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTraditionalDress Context triple: [Songkran, hasTraditionalDress, colorful floral shirts]
-
A.
hasDressCode
Indicates that a specified entity enforces or is associated with a particular set of rules governing appropriate clothing or attire.
-
B.
hasTraditionalSymbol
Indicates that something is associated with or represented by a conventional or culturally established symbol.
-
C.
garmentType
Indicates the specific kind or category of garment associated with an entity.
-
D.
hasCulturalFeature
chosen
Indicates that an entity possesses, includes, or is characterized by a particular cultural element, attribute, or landmark.
-
E.
ceremonialDressFeature
Indicates that one entity is a characteristic, component, or distinguishing element of another entity’s ceremonial dress or attire.
- 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_69a49369a0848190af883934cee3db4c |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a74da7648190adfad56717d564df |
completed | March 1, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69a4a50a443481909ae3662764ee69a4 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.