Triple
T12575335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | วัดอรุณ |
E300190
|
entity |
| Predicate | มีพระปรางค์ราย |
P32932
|
FINISHED |
| Object | 4 องค์ล้อมพระปรางค์ประธาน |
—
|
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: 4 องค์ล้อมพระปรางค์ประธาน | Statement: [วัดอรุณ, มีพระปรางค์ราย, 4 องค์ล้อมพระปรางค์ประธาน]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: มีพระปรางค์ราย Context triple: [วัดอรุณ, มีพระปรางค์ราย, 4 องค์ล้อมพระปรางค์ประธาน]
-
A.
hasPagoda
chosen
Indicates that one entity possesses, contains, or is characterized by the presence of a pagoda.
-
B.
hasFiveStoryPagoda
Indicates that an entity possesses or includes a pagoda structure specifically consisting of five stories.
-
C.
hasTempleOf
Indicates that a location or entity possesses, contains, or is the site of a temple dedicated to a particular deity, figure, or purpose.
-
D.
hasNumberOfPrakaras
Indicates the relationship specifying how many prakaras (enclosure layers or surrounding structures) are associated with a given entity.
-
E.
hasTempleCount
Indicates that an entity is associated with a specified number of temples.
- 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.