Triple
T4695182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United Nations official languages |
E104124
|
entity |
| Predicate | includes |
P1393
|
FINISHED |
| Object | Russian |
E3584
|
NE 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: Russian | Statement: [United Nations official languages, includes, Russian]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Russian Context triple: [United Nations official languages, includes, Russian]
-
A.
Russin
Russin is a small wine-producing municipality and village located in the canton of Geneva in southwestern Switzerland.
-
B.
Russian language
chosen
Russian is an East Slavic language spoken primarily in Russia and neighboring countries, serving as one of the world's major languages in politics, science, and culture.
-
C.
RU
RU is the common abbreviation for Radboud University Nijmegen, a major research university located in Nijmegen, the Netherlands.
-
D.
RU
RU is the common abbreviation for Rutgers University, a major public research institution in New Jersey.
-
E.
RU
RU is the historic vehicle registration code that was used for the English county of Rutland.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69bd43df91f481908e9add1b617b60ef |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd63b1cee481908a8fb5eeb359cc00 |
completed | March 20, 2026, 3:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be03c093ac8190869aab6abcfd571f |
completed | March 21, 2026, 2:34 a.m. |
Created at: March 20, 2026, 1:17 p.m.