Triple
T6340821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | חַנָּה |
E142618
|
entity |
| Predicate | relatedName |
P3889
|
FINISHED |
| Object | Anya |
unclear NED1
|
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: [חַנָּה, relatedName, Anya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anya Context triple: [חַנָּה, relatedName, 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
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.
Natalya
Natalya is a feminine given name of Slavic origin, commonly used in Russian-speaking countries and derived from the Latin name Natalia.
-
E.
Yelena
Yelena is a feminine given name of Slavic origin, commonly used in Russian-speaking countries and equivalent to Helen or Helena in English.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69c008d5ab108190b346c465696824a9 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0674311388190bb069a07a7ff60ef |
completed | March 22, 2026, 10:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6043afb4081908d480ad868625909 |
completed | March 27, 2026, 4:14 a.m. |
Created at: March 22, 2026, 4:30 p.m.