Triple
T12575355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | วัดอรุณ |
E300190
|
entity |
| Predicate | ดึงดูด |
P1347
|
FINISHED |
| Object | นักท่องเที่ยวทั้งชาวไทยและชาวต่างชาติ |
—
|
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: นักท่องเที่ยวทั้งชาวไทยและชาวต่างชาติ | Statement: [วัดอรุณ, ดึงดูด, นักท่องเที่ยวทั้งชาวไทยและชาวต่างชาติ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ดึงดูด Context triple: [วัดอรุณ, ดึงดูด, นักท่องเที่ยวทั้งชาวไทยและชาวต่างชาติ]
-
A.
attracts
chosen
Indicates that one entity exerts a force or influence that draws another entity toward it.
-
B.
traction
Indicates the degree to which one entity’s movement or influence effectively grips, pulls, or gains momentum relative to another entity or medium.
-
C.
deathAttracting
Indicates a relationship where one entity’s death draws, lures, or otherwise causes another entity to come closer or be attracted.
-
D.
succeededByAttraction
Indicates that one attraction or point of interest is directly followed or replaced by another attraction in a sequence or timeline.
-
E.
attractsAudience
Indicates that an entity draws the interest or attention of people who choose to watch, listen to, or engage with it.
- 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.