Triple
T12575337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | วัดอรุณ |
E300190
|
entity |
| Predicate | มีพระวิหาร |
P64892
|
FINISHED |
| Object | ใช้ประกอบศาสนพิธี |
—
|
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: ใช้ประกอบศาสนพิธี | Statement: [วัดอรุณ, มีพระวิหาร, ใช้ประกอบศาสนพิธี]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: มีพระวิหาร Context triple: [วัดอรุณ, มีพระวิหาร, ใช้ประกอบศาสนพิธี]
-
A.
hasTempleOf
chosen
Indicates that a location or entity possesses, contains, or is the site of a temple dedicated to a particular deity, figure, or purpose.
-
B.
containsCathedral
Indicates that one entity includes or has within its boundaries a cathedral associated with it.
-
C.
hasNotableTemple
Indicates that an entity is associated with a temple that is recognized as particularly important, famous, or significant.
-
D.
containsMonastery
Indicates that one entity includes or encompasses a monastery within its boundaries or composition.
-
E.
hasVicariate
Indicates that one entity serves as a vicariate (a delegated or substitute authority or jurisdiction) for another entity.
- 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_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. |
Created at: April 9, 2026, 4:46 p.m.