Triple
T18066097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maiduan |
E432296
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Konkow 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: Konkow language | Statement: [Maiduan, hasPart, Konkow language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Konkow language Context triple: [Maiduan, hasPart, Konkow language]
-
A.
Konkow language
chosen
The Konkow language is an endangered Native American language traditionally spoken by the Konkow (Koyom’kawi) people of northern California.
-
B.
Konda-Dora language
Konda-Dora language is a Dravidian tribal language spoken primarily by the Konda Dora people in parts of Andhra Pradesh and Odisha in India.
-
C.
Kumbewaha language
The Kumbewaha language is an Austronesian language spoken in Sulawesi, Indonesia, belonging to the Wotu–Wolio subgroup.
-
D.
Kunwinjku language
Kunwinjku language is an Australian Aboriginal language of the Bininj people, spoken primarily in western Arnhem Land in the Northern Territory.
-
E.
Teke-Kukuya language
The Teke-Kukuya language is a Bantu language spoken by the Teke-Kukuya people in the Republic of the Congo and neighboring regions of Central Africa.
- 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_69d8b9070cac81909fa9473fb1c3f1c7 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4cce97ce08190a2f8762ce545e091 |
completed | April 19, 2026, 12:39 p.m. |
Created at: April 10, 2026, 10:26 a.m.