Triple
T11090370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aleksandra Khokhlova |
E262234
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Aelita |
E517007
|
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: Aelita | Statement: [Aleksandra Khokhlova, notableWork, Aelita]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aelita Context triple: [Aleksandra Khokhlova, notableWork, Aelita]
-
A.
Aelita
chosen
Aelita is a pioneering early Soviet science fiction novel by Alexei Tolstoy that tells the story of a journey to Mars and a revolutionary uprising there.
-
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.
A'Lars
A'Lars, also known as Mentor, is an Eternal from Titan and the father of Thanos in Marvel Comics.
-
D.
V’Ger
V’Ger is the immensely powerful, evolved space probe that serves as the central enigmatic antagonist in the film "Star Trek: The Motion Picture."
-
E.
Rammu
Rammu is a small Estonian island in the Gulf of Finland, known for its natural landscapes and sparse habitation.
- 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_69d6aa9a40d88190a373e2c7e48285db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d799e96ca08190838c8a04d1eb2a16 |
completed | April 9, 2026, 12:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3e7c586808190a576803b7406a49e |
completed | April 18, 2026, 8:21 p.m. |
Created at: April 8, 2026, 9:27 p.m.