Triple
T24309991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kamassian |
E612644
|
entity |
| Predicate | lastNativeSpeakerName |
P23806
|
FINISHED |
| Object | Klavdiya Plotnikova |
—
|
NE NERFINISHED |
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: Klavdiya Plotnikova | Statement: [Kamassian, lastNativeSpeakerName, Klavdiya Plotnikova]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lastNativeSpeakerName Context triple: [Kamassian, lastNativeSpeakerName, Klavdiya Plotnikova]
-
A.
lastTraditionalNativeSpeakerOftenCitedAs
Indicates that the subject is widely regarded or referenced as the last traditional native speaker of the language or dialect in question.
-
B.
lastNativeSpeakersDiedOut
Indicates that the final remaining native speakers of a language or dialect have died, resulting in the loss of native speech for that language.
-
C.
lastKnownSpeaker
chosen
Indicates the entity that was most recently identified or recorded as speaking in a given context or interaction.
-
D.
hasNativeSpeakers
Indicates that a language or dialect is spoken as a first language by one or more people or populations.
-
E.
hasNotablePersonWithSurname
Indicates that an entity is associated with at least one notable person who bears a specified surname.
- F. None of above.
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_69e2d7d91bb48190bc5377d17a85fb21 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f29229af3c8190950b70fe5a8dbf6f |
completed | April 29, 2026, 11:20 p.m. |
| PD | Predicate disambiguation | batch_69f1c45c6ec081908401b69424428100 |
completed | April 29, 2026, 8:42 a.m. |
Created at: April 18, 2026, 1:33 a.m.