Triple
T20899469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tofa language |
E514630
|
entity |
| Predicate | alternativeName |
P39
|
FINISHED |
| Object | Tofa |
—
|
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: Tofa | Statement: [Tofa language, alternativeName, Tofa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tofa Context triple: [Tofa language, alternativeName, Tofa]
-
A.
Tofa
chosen
Tofa is a critically endangered Turkic language spoken by a small indigenous community in Siberia, Russia.
-
B.
Tufan
Tufan is a Turkish surname most notably associated with professional footballer Ozan Tufan.
-
C.
Mosina
Mosina is an alternative name for Vurës, a language spoken on the island of Vanua Lava in Vanuatu.
-
D.
Warhad
Warhad is an old regional name historically used for the area later known as Berar in central India.
-
E.
Tatoga
Tatoga are a Nilotic-speaking pastoralist ethnic group primarily inhabiting north-central Tanzania, known for their traditional herding lifestyle and distinctive cultural practices.
- 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_69e0b4f8a1108190bce3d31331290ced |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6e8f92bd88190b59b2131ad1d9aa1 |
completed | April 21, 2026, 3:03 a.m. |
Created at: April 16, 2026, 12:47 p.m.