Triple
T16950698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belarusian Pahonia |
E411171
|
entity |
| Predicate | statusInBelarus |
P125354
|
FINISHED |
| Object | not official state emblem since 1995 referendum |
—
|
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: not official state emblem since 1995 referendum | Statement: [Belarusian Pahonia, statusInBelarus, not official state emblem since 1995 referendum]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: statusInBelarus Context triple: [Belarusian Pahonia, statusInBelarus, not official state emblem since 1995 referendum]
-
A.
statusInRussia
Indicates the legal, social, or operational condition or standing that something or someone has specifically within the context of Russia.
-
B.
statusOfVilnius
Indicates the current political or administrative status or condition assigned to Vilnius.
-
C.
statusInLatvia
Indicates the legal, social, or official condition or standing that something or someone has within the context of Latvia.
-
D.
statusInZimbabwe
Indicates the legal, social, or official standing or condition that an entity holds within the context of Zimbabwe.
-
E.
estatusEnUruguay
Indicates the legal or official status that an entity holds within Uruguay.
- 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_69d886c9c9d481909afe222093641cae |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3cfb6e5fc8190b1bd3ad1c2773685 |
completed | April 18, 2026, 6:38 p.m. |
| PD | Predicate disambiguation | batch_69e32b9aa8748190b248890aca86753d |
completed | April 18, 2026, 6:58 a.m. |
| PDg | Predicate description generation | batch_69e355722040819098830dabf207ecd6 |
completed | April 18, 2026, 9:57 a.m. |
Created at: April 10, 2026, 5:31 a.m.