Triple
T9099724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orang Asli |
E218121
|
entity |
| Predicate | populationPercentageInMalaysia |
P87148
|
FINISHED |
| Object | less than 1 percent |
—
|
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: less than 1 percent | Statement: [Orang Asli, populationPercentageInMalaysia, less than 1 percent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: populationPercentageInMalaysia Context triple: [Orang Asli, populationPercentageInMalaysia, less than 1 percent]
-
A.
areaRankInMalaysia
Indicates the relative position of an entity in a size-based ranking by area within Malaysia.
-
B.
politicalStatusInMalaysia
Indicates the political role, position, or standing that an entity holds within the political system or context of Malaysia.
-
C.
rankingByLengthInPeninsularMalaysia
Indicates a ranking relationship among items based on their lengths, specifically within the context of Peninsular Malaysia.
-
D.
statusInMalaysia
Indicates the legal, social, or official standing or condition an entity holds specifically within the context of Malaysia.
-
E.
nearCityOnMalaysianSide
Indicates that one entity is located close to a particular city that lies on the Malaysian side of a border or region.
- 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_69ca83d9844081908e561e367fda6d45 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc9710ac04819096b9c8d3399b9c35 |
completed | April 1, 2026, 3:54 a.m. |
| PD | Predicate disambiguation | batch_69cc65fc7f408190a5846e29ab3b97e5 |
completed | April 1, 2026, 12:25 a.m. |
| PDg | Predicate description generation | batch_69cc6a3c78388190a7436acc0e44ff55 |
completed | April 1, 2026, 12:43 a.m. |
Created at: March 30, 2026, 7:15 p.m.