Triple
T15330046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anastasia |
E366508
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Anya |
E563376
|
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: Anya | Statement: [Anastasia, mainCharacter, Anya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anya Context triple: [Anastasia, mainCharacter, Anya]
-
A.
Anya
Anya is a person known primarily through her relationship to someone named Hannah, likely as a friend or family member.
-
B.
Anya
Anya is the given name of actress Anya Taylor-Joy, known for her roles in films like "The Witch" and the series "The Queen's Gambit."
-
C.
Anya
chosen
Anya is the spirited, amnesiac young woman in the animated film "Anastasia" who embarks on a journey to discover whether she is the lost Russian Grand Duchess.
-
D.
Anya
Anya is a novel by Joy Davidman, best known as a work of mid-20th-century fiction by the poet and writer who later married C. S. Lewis.
-
E.
Anya Taranda
Anya Taranda was an American fashion model and actress best known for her work in the 1930s and 1940s.
- 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_69d85a121520819093dcce999fdefe1a |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e0161ac8190aa1d52c063c02ad0 |
completed | April 16, 2026, 1:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fef8b1b2d08190a158bf65535ad750 |
completed | May 9, 2026, 9:04 a.m. |
Created at: April 10, 2026, 3:17 a.m.