Triple
T26718610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thailand administrative divisions |
E673634
|
entity |
| Predicate | hasNumberOfAdministrativeRegions |
P2355
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [Thailand administrative divisions, hasNumberOfAdministrativeRegions, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfAdministrativeRegions Context triple: [Thailand administrative divisions, hasNumberOfAdministrativeRegions, 6]
-
A.
hasMultipleAdministrativeCenters
Indicates that an entity is administered from more than one official administrative center or capital.
-
B.
hasNumberOfProvinces
Indicates the total count of provinces associated with a given entity.
-
C.
hasNumberOfMunicipalities
Indicates the relationship that specifies how many municipalities are associated with or contained within a given administrative or geographic entity.
-
D.
numberOfRegions
chosen
Indicates the total count of distinct regions associated with or contained within a given entity.
-
E.
hasNumberOfStatesAndDistricts
Indicates a relationship where an entity is associated with a specific count of its constituent states and districts.
- 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_69eecda481d08190aea69f2f7c745f56 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f7308a096081909d66a56f3c926806 |
completed | May 3, 2026, 11:24 a.m. |
| PD | Predicate disambiguation | batch_69f72a00c5f081908b6539d15baf4e12 |
completed | May 3, 2026, 10:57 a.m. |
Created at: April 27, 2026, 3:39 a.m.