Triple
T30724950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Perlis |
E782252
|
entity |
| Predicate | areaRankingInMalaysia |
P33341
|
FINISHED |
| Object | smallest state |
—
|
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: smallest state | Statement: [Perlis, areaRankingInMalaysia, smallest state]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areaRankingInMalaysia Context triple: [Perlis, areaRankingInMalaysia, smallest state]
-
A.
areaRankInMalaysia
chosen
Indicates the relative position of an entity in a size-based ranking by area within Malaysia.
-
B.
regionInMalaysia
Indicates that a region or area is located within the country of Malaysia.
-
C.
rankingByLengthInPeninsularMalaysia
Indicates a ranking relationship among items based on their lengths, specifically within the context of Peninsular Malaysia.
-
D.
populationPercentageInMalaysia
Indicates the proportion of a given population that resides in Malaysia, expressed as a percentage.
-
E.
hasAreaRankInTaiwan
Indicates the relative ranking of an entity by its area size compared to other entities within Taiwan.
- 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_69f224ad9f9c81908e02a79ae0001137 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f68c5bab9c8190b1f0518559c5259f |
completed | May 2, 2026, 11:44 p.m. |
| PD | Predicate disambiguation | batch_69f6861170d08190bb98be609d436f84 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 29, 2026, 8:36 p.m.