Triple
T15276608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tatyana Dyachenko |
E365156
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Tatyana |
E68776
|
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: Tatyana | Statement: [Tatyana Dyachenko, givenName, Tatyana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tatyana Context triple: [Tatyana Dyachenko, givenName, Tatyana]
-
A.
Tatyana
chosen
Tatyana is a feminine given name of Slavic origin, particularly common in Russian-speaking countries.
-
B.
Наташа
Наташа — одна из главных героинь пьесы Максима Горького «На дне», олицетворяющая трагическую судьбу бедной и угнетённой женщины в мире социального дна.
-
C.
Nadezhda Vasilyeva
Nadezhda Vasilyeva is known primarily as a daughter of Vasily Stalin, the son of Soviet leader Joseph Stalin.
-
D.
Nadezhda Vasilyeva
Nadezhda Vasilyeva is a costume designer known for her work on the film "Two Women."
-
E.
Tatyana Larina
Tatyana Larina is the introspective and emotionally sincere heroine of Alexander Pushkin’s novel in verse "Eugene Onegin," often regarded as one of Russian literature’s most iconic female characters.
- 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_69d85a103d9081908c1ea6c4c73ac8e3 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e00953bc848190b83919f39d5ee37b |
completed | April 15, 2026, 9:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff01e092408190aec1561e78ea0acb |
completed | May 9, 2026, 9:44 a.m. |
Created at: April 10, 2026, 3:14 a.m.