Triple
T12841662
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Makha Bucha |
E307064
|
entity |
| Predicate | workStatusInThailand |
P107168
|
FINISHED |
| Object | most government offices closed |
—
|
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: most government offices closed | Statement: [Makha Bucha, workStatusInThailand, most government offices closed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workStatusInThailand Context triple: [Makha Bucha, workStatusInThailand, most government offices closed]
-
A.
statusInThailand
Indicates the legal, social, or official standing or condition an entity holds specifically within the context of Thailand.
-
B.
worksStatus
Indicates the current state or condition of an entity’s work or project, such as whether it is planned, in progress, completed, or otherwise categorized.
-
C.
workStatusInMexico
Indicates whether an entity is authorized to work or is currently working in Mexico.
-
D.
workStatusInIsrael
Indicates the employment or legal work authorization status a person holds within Israel.
-
E.
statusInMalaysia
Indicates the legal, social, or official standing or condition an entity holds specifically within the context of Malaysia.
- F. None of above. chosen
Provenance (4 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_69d7bdf52b94819096d6f0ba4ab50a98 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9714208f881908f7f8a921362909a |
completed | April 10, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69d96fa08cd481909a946046ba63809f |
completed | April 10, 2026, 9:46 p.m. |
| PDg | Predicate description generation | batch_69d9713e45a88190acd346f066093550 |
completed | April 10, 2026, 9:53 p.m. |
Created at: April 9, 2026, 5:35 p.m.