Triple
T12575349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | วัดอรุณ |
E300190
|
entity |
| Predicate | การแต่งกายเข้าชม |
P105504
|
FINISHED |
| Object | ต้องแต่งกายสุภาพ |
—
|
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: ต้องแต่งกายสุภาพ | Statement: [วัดอรุณ, การแต่งกายเข้าชม, ต้องแต่งกายสุภาพ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: การแต่งกายเข้าชม Context triple: [วัดอรุณ, การแต่งกายเข้าชม, ต้องแต่งกายสุภาพ]
-
A.
usualAttire
Indicates the type of clothing an entity typically wears in ordinary or characteristic situations.
-
B.
ceremonialDressFeature
Indicates that one entity is a characteristic, component, or distinguishing element of another entity’s ceremonial dress or attire.
-
C.
usesDressing
Indicates that one entity applies or employs a particular dressing (such as a sauce, covering, or treatment) in relation to another entity or context.
-
D.
checkInStyle
Indicates that an entity arrives or registers at a place or event in a notably fashionable or impressive manner.
-
E.
costume
Indicates that one entity is wearing, dressed in, or outfitted with the other entity as a costume.
- F. None of above. chosen
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_69d7bde87b648190bcd0266e9efde098 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9550d84908190aea0f50055f6d92e |
completed | April 10, 2026, 7:52 p.m. |
| PD | Predicate disambiguation | batch_69d95414692881909c52a1de7d224b44 |
completed | April 10, 2026, 7:48 p.m. |
| PDg | Predicate description generation | batch_69d9550af6d48190a40e349ed0424be3 |
completed | April 10, 2026, 7:52 p.m. |
Created at: April 9, 2026, 4:46 p.m.