Triple
T35857566
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United Democratic Alliance |
E1036550
|
entity |
| Predicate | prominentIssue |
P57423
|
FINISHED |
| Object | economic empowerment of low-income workers |
—
|
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: economic empowerment of low-income workers | Statement: [United Democratic Alliance, prominentIssue, economic empowerment of low-income workers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: prominentIssue Context triple: [United Democratic Alliance, prominentIssue, economic empowerment of low-income workers]
-
A.
primaryIssue
chosen
Indicates that the related item is the main or most important issue among a set of issues.
-
B.
notableModernIssue
Indicates that the subject is recognized as a significant or widely discussed issue in contemporary times.
-
C.
notableEarlyIssue
Indicates that the subject is a significant or noteworthy early edition, release, or version of the object.
-
D.
majorIssue
Indicates that something is a primary or most significant problem, concern, or obstacle in a given context.
-
E.
mainTitleIssues
Indicates that there are problems or concerns specifically related to the main title of an item, work, or record.
- 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_69f76e1b4aa481909630373171eb5ec6 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7b5ccbda481908fe1945c35e36ce8 |
completed | May 3, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69f7b4c06f5881908f0b98cad6796478 |
completed | May 3, 2026, 8:49 p.m. |
Created at: May 3, 2026, 4:06 p.m.