Triple
T4198092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Call of Duty: Modern Warfare 3 |
E86000
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object | Yuri |
E40856
|
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: Yuri | Statement: [Call of Duty: Modern Warfare 3, hasCharacter, Yuri]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yuri Context triple: [Call of Duty: Modern Warfare 3, hasCharacter, Yuri]
-
A.
Yuri
chosen
Yuri is a common Russian given name, famously borne by Yuri Gagarin, the first human to journey into outer space.
-
B.
Lyova
Lyova is a Russian diminutive form of the male given name Lev.
-
C.
Aloysya
Aloysya is a given name, typically a feminine variant of Aloysius, used in various cultures and languages.
-
D.
Ruzan
Ruzan is a surname most notably associated with American television producer and writer Robin Ruzan.
-
E.
Yunaska
Yunaska is the maiden surname of Lara Trump, who is married to Eric Trump, son of former U.S. President Donald Trump.
- 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_69aed93b89f48190a31f6d57c760e42f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af0360bc8081908ceb2483eef89174 |
completed | March 9, 2026, 5:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5a84d00b8819082982c4d229c450e |
completed | March 14, 2026, 6:26 p.m. |
Created at: March 9, 2026, 3:48 p.m.