Triple
T26641060
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ยี่เป็ง |
E668779
|
entity |
| Predicate | จัดขึ้นในประเทศ |
P117234
|
FINISHED |
| Object | ประเทศไทย |
—
|
NE NERFINISHED |
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: ประเทศไทย | Statement: [ยี่เป็ง, จัดขึ้นในประเทศ, ประเทศไทย]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: จัดขึ้นในประเทศ Context triple: [ยี่เป็ง, จัดขึ้นในประเทศ, ประเทศไทย]
-
A.
tookPlaceInPresentDayCountry
Indicates that an event or occurrence happened within the geographic area of the country as it is defined in the present day.
-
B.
isSetInCountry
chosen
Indicates that something (such as an event, story, or scene) takes place within the geographical or political boundaries of a specified country.
-
C.
meetsInCountry
Indicates that two or more entities have an in-person meeting that takes place within the specified country.
-
D.
organizerCountry
Indicates the country that serves as the organizer or host for an event, activity, or initiative.
-
E.
countryOfVenue
Indicates the country in which the referenced venue is geographically located.
- 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_69ee9d0024b8819090a7c8cf669a3b6c |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f62d53ad58819080c5227c7a729d15 |
completed | May 2, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69f62c15952881908a5ea0c25904afec |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 27, 2026, 2:29 a.m.