Triple
T29531522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samut Songkhram |
E749215
|
entity |
| Predicate | isSmallestProvinceByAreaIn |
P14659
|
FINISHED |
| Object | Thailand |
—
|
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: Thailand | Statement: [Samut Songkhram, isSmallestProvinceByAreaIn, Thailand]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isSmallestProvinceByAreaIn Context triple: [Samut Songkhram, isSmallestProvinceByAreaIn, Thailand]
-
A.
isSmallestByAreaIn
chosen
Indicates that an entity has the smallest area among all comparable entities within a specified set, group, or context.
-
B.
isSmallestCountryIn
Indicates that a country is the smallest (by a specified measure, typically area) among all countries within a given region or set.
-
C.
isSmallestLocalGovernmentUnitIn
Indicates that one administrative unit is the smallest (most localized) level of government within the specified larger territorial or political area.
-
D.
smallestRegionByPopulation
Indicates that the subject is the region with the lowest population among a specified set of regions.
-
E.
isOneOfLargestProvincesByAreaIn
Indicates that a province is among the largest provinces by land area within a specified region or country.
- 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_69f0bd47abb081909bd6e6a33d770fd8 |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69f66cc2656081908adb6f119caa0cc1 |
completed | May 2, 2026, 9:29 p.m. |
| PD | Predicate disambiguation | batch_69f6659d36208190b01412600a4ed57d |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 28, 2026, 4:53 p.m.