Triple
T20703496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dane-zaa |
E508840
|
entity |
| Predicate | traditionalLanguage |
P6149
|
FINISHED |
| Object | Dane-zaa language |
—
|
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: Dane-zaa language | Statement: [Dane-zaa, traditionalLanguage, Dane-zaa language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dane-zaa language Context triple: [Dane-zaa, traditionalLanguage, Dane-zaa language]
-
A.
Dane-zaa language
chosen
The Dane-zaa language is an Athabaskan (Dene) language traditionally spoken by the Dane-zaa people of northeastern British Columbia and northwestern Alberta in Canada.
-
B.
Daakaka language
The Daakaka language is an Oceanic language spoken by communities on Ambrym Island in Vanuatu.
-
C.
Damana language
The Damana language is an indigenous Chibchan tongue spoken by the Wiwa people of the Sierra Nevada de Santa Marta region in northern Colombia.
-
D.
Gupa-Abawa language
The Gupa-Abawa language is a Nupoid language spoken by the Gupa and Abawa peoples of central Nigeria.
-
E.
Datooga language
The Datooga language is a Southern Nilotic language spoken by the Datooga people of north-central Tanzania, known for its complex dialect diversity and rich oral tradition.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4c2b2a481909e31e9cb8f81ab55 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6c18dbda081908217dcb61cbf7ba4 |
completed | April 21, 2026, 12:15 a.m. |
Created at: April 16, 2026, 12:13 p.m.