Triple
T21662655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tuvans |
E534630
|
entity |
| Predicate | demographicStatusInTuva |
P94260
|
FINISHED |
| Object | majority population |
—
|
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: majority population | Statement: [Tuvans, demographicStatusInTuva, majority population]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: demographicStatusInTuva Context triple: [Tuvans, demographicStatusInTuva, majority population]
-
A.
demographicStatusInRomania
Indicates the demographic status or classification of an entity within the population context of Romania.
-
B.
demographicScope
Indicates the specific population group or demographic segment to which something (e.g., a policy, study, product, or service) is targeted or applicable.
-
C.
hasPopulationStatus
Indicates the current demographic condition or classification of a population associated with an entity.
-
D.
demographicBasis
Indicates that something is determined, classified, or justified based on demographic characteristics such as age, gender, ethnicity, or similar population attributes.
-
E.
demographicsIn
chosen
Indicates that demographic information is associated with or applies within a specified geographic or organizational area.
- 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_69e0c467e1f48190af2650b19175abc4 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef6c0956e0819093b4794418efe052 |
completed | April 27, 2026, 2 p.m. |
| PD | Predicate disambiguation | batch_69e696826c3c81909270791e79760937 |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:36 p.m.