Triple
T38621152
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parti Rakyat Malaysia |
E936870
|
entity |
| Predicate | hasEthnicPolicy |
P193640
|
FINISHED |
| Object | multi-ethnic membership |
—
|
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: multi-ethnic membership | Statement: [Parti Rakyat Malaysia, hasEthnicPolicy, multi-ethnic membership]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEthnicPolicy Context triple: [Parti Rakyat Malaysia, hasEthnicPolicy, multi-ethnic membership]
-
A.
ethnicPolicyContext
Indicates the policy framework, conditions, or circumstances specifically related to ethnic groups within which an action, decision, or relationship occurs.
-
B.
hasEthnicTarget
Indicates that an action, statement, or event is directed toward or targets a specific ethnic group.
-
C.
hasEthnicOrNationalComposition
Indicates that an entity is characterized by a particular ethnic or national group composition.
-
D.
hasEthnicDivision
Indicates that a group, region, or entity is characterized by internal divisions or distinctions based on ethnicity.
-
E.
hasEthnicEducation
Indicates that an entity provides, includes, or is associated with education specifically focused on ethnic groups, cultures, or identities.
- 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_69f76ed403208190b862dc795171353f |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fd4d1854988190be093b103a681798 |
completed | May 8, 2026, 2:40 a.m. |
| PD | Predicate disambiguation | batch_69fd4c8d1a188190897c24527337814a |
completed | May 8, 2026, 2:38 a.m. |
| PDg | Predicate description generation | batch_69fd4d16dd20819096957c40f43cd971 |
completed | May 8, 2026, 2:40 a.m. |
Created at: May 3, 2026, 4:32 p.m.