Triple
T19624241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Olga Larina |
E471091
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Larina |
—
|
NE NERFINISHED |
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: Larina | Statement: [Olga Larina, familyName, Larina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Larina Context triple: [Olga Larina, familyName, Larina]
-
A.
Larina
chosen
Larina is a Russian surname most notably borne by Anna Larina, the widow of Bolshevik leader Nikolai Bukharin.
-
B.
Yuriatin
Yuriatin is a fictional Russian town in Boris Pasternak’s novel "Doctor Zhivago," serving as a key setting in Yuri Zhivago’s life and relationships.
-
C.
Marliana
Marliana is a small Italian municipality in the Tuscany region, known for its hilly landscape and historic rural character.
-
D.
Love, Antosha
Love, Antosha is a 2019 documentary film that chronicles the life and career of actor Anton Yelchin through home videos, interviews, and personal writings.
-
E.
Chaika
Chaika was the radio callsign used by Soviet cosmonaut Valentina Tereshkova during her historic 1963 Vostok 6 mission as the first woman in space.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e510fa248190b7afb274a1d4cf73 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e640e8695c81909268c5a91cdbb7fa |
completed | April 20, 2026, 3:06 p.m. |
Created at: April 10, 2026, 1:44 p.m.