Triple
T21500230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kogi language |
E530454
|
entity |
| Predicate | closelyRelatedTo |
P37
|
FINISHED |
| Object | Damana 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: Damana language | Statement: [Kogi language, closelyRelatedTo, Damana language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Damana language Context triple: [Kogi language, closelyRelatedTo, Damana language]
-
A.
Damana language
chosen
The Damana language is an indigenous Chibchan tongue spoken by the Wiwa people of the Sierra Nevada de Santa Marta region in northern Colombia.
-
B.
Tanema language
Tanema is a nearly extinct Oceanic language once spoken on Vanikoro Island in the Temotu Province of the Solomon Islands.
-
C.
Damara language
The Damara language is a Khoe (Central Khoisan) language spoken primarily by the Damara people of Namibia.
-
D.
Badimaya language
Badimaya language is an Australian Aboriginal language traditionally spoken by the Yamatji people of Western Australia.
-
E.
Daakaka language
The Daakaka language is an Oceanic language spoken by communities on Ambrym Island in Vanuatu.
- 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_69e0c45bd15481909fba5910765cdda2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea5ae154819090299773b373b921 |
completed | April 23, 2026, 9:46 a.m. |
Created at: April 16, 2026, 6:24 p.m.