Triple
T26894502
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saraikis |
E677862
|
entity |
| Predicate | demographicStatusInPakistan |
P16668
|
FINISHED |
| Object | minority group |
—
|
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: minority group | Statement: [Saraikis, demographicStatusInPakistan, minority group]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: demographicStatusInPakistan Context triple: [Saraikis, demographicStatusInPakistan, minority group]
-
A.
populationRankInPakistan
Indicates the relative position of an entity in terms of its population size compared to other entities within Pakistan.
-
B.
statusInPakistan
chosen
Indicates the legal, social, or operational condition or standing that something or someone has within the context of Pakistan.
-
C.
areaRankInPakistan
Indicates the relative position of an entity when all entities in Pakistan are ordered by their area size.
-
D.
demographicBasis
Indicates that something is determined, classified, or justified based on demographic characteristics such as age, gender, ethnicity, or similar population attributes.
-
E.
demographics
Indicates the relationship of providing or characterizing statistical information about a population’s attributes, such as age, gender, income, or education.
- 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_69eee9befee48190a26f214faa867be7 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f61f6ac6ac8190be96a4211305dbbe |
completed | May 2, 2026, 3:59 p.m. |
| PD | Predicate disambiguation | batch_69f611af72ac819094598dd2530d7411 |
completed | May 2, 2026, 3:01 p.m. |
Created at: April 27, 2026, 5:47 a.m.