Triple
T15537544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Masha |
E370387
|
entity |
| Predicate | scriptForm |
P9329
|
FINISHED |
| Object | Маша |
E370387
|
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: Маша | Statement: [Masha, scriptForm, Маша]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Маша Context triple: [Masha, scriptForm, Маша]
-
A.
Masha
chosen
Masha is a diminutive and affectionate Russian form of the given name Mary (Maria).
-
B.
Masha
Masha is a town in southwestern Ethiopia that serves as an administrative and commercial center in the Sheka Zone.
-
C.
Marichka
Marichka is a key supporting character in the dystopian film "Children of Men," known for helping protect the first pregnant woman in years.
-
D.
Sashenka
Sashenka is a Russian diminutive form of the given name Aleksandr (Alexander), often used as an affectionate nickname.
-
E.
Mila
Mila is the nickname of Margaret Laura Hager, the granddaughter of former U.S. President George W. Bush.
- 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_69d85cc521a08190921fb50319dddc34 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e0442f3c688190a599165e526af2ed |
completed | April 16, 2026, 2:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3d626e688190bd93481cfd6cb255 |
completed | May 9, 2026, 1:57 p.m. |
Created at: April 10, 2026, 4:06 a.m.