Triple
T12575352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | วัดอรุณ |
E300190
|
entity |
| Predicate | มีชื่อเกี่ยวข้องกับ |
P24023
|
FINISHED |
| Object | อรุณรุ่งและแสงแรกของวัน |
—
|
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: อรุณรุ่งและแสงแรกของวัน | Statement: [วัดอรุณ, มีชื่อเกี่ยวข้องกับ, อรุณรุ่งและแสงแรกของวัน]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: มีชื่อเกี่ยวข้องกับ Context triple: [วัดอรุณ, มีชื่อเกี่ยวข้องกับ, อรุณรุ่งและแสงแรกของวัน]
-
A.
mentionedWith
Indicates that two entities are mentioned together or in close association within the same context, such as a document, sentence, or conversation.
-
B.
relatedNamedEntity
Indicates that two entities are connected through a shared or associated proper name (e.g., person, organization, location, or other named entity).
-
C.
mayBeInvolvedIn
Indicates that an entity has a possible, but not certain, participation or role in a particular event, activity, or situation.
-
D.
associatedName
chosen
Indicates that one entity has an alternative or related name that is linked or connected to another entity.
-
E.
isRelatedName
Indicates that one name is connected to another through a variant, derivative, or otherwise non-identical but related naming relationship.
- 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.