Triple
T2581801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Volga region |
E57107
|
entity |
| Predicate | hasEthnicGroup |
P1898
|
FINISHED |
| Object | Mari |
E250766
|
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: Mari | Statement: [Volga region, hasEthnicGroup, Mari]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mari Context triple: [Volga region, hasEthnicGroup, Mari]
-
A.
Mari
Mari is a character in Paulo Coelho's novel "Veronika Decides to Die," portrayed as a fellow patient in the mental institution who struggles with anxiety and societal expectations.
-
B.
Mari
chosen
Mari is a Uralic language spoken by the Mari people, primarily in the Mari El Republic of Russia.
-
C.
Marla
Marla is a feminine given name most notably borne by American actress and television personality Marla Maples.
-
D.
Mir
Mir is a traditional South Asian noble title historically used by rulers and aristocrats, particularly in regions such as Sindh under dynasties like the Talpurs.
-
E.
Mir
Mir was a Soviet and later Russian modular space station that served as a long-term research outpost in low Earth orbit from 1986 to 2001.
- 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_69ab4a4dca6481908c301f8e317396e7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd3c843bc8190837cea3441bf3ca1 |
completed | March 7, 2026, 7:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af657cc2b08190a9055d6da7744851 |
completed | March 10, 2026, 12:27 a.m. |
Created at: March 6, 2026, 9:49 p.m.