Triple
T22851385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northern Ryukyuan language |
E566363
|
entity |
| Predicate | hasVariety |
P455
|
FINISHED |
| Object |
Kikai language
The Kikai language is a Ryukyuan language spoken on Kikai Island in Japan’s Kagoshima Prefecture, known for its distinct dialectal variation and endangered status.
|
E1556704
|
NE FINISHED |
How this triple was built (4 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: Kikai language | Statement: [Northern Ryukyuan language, hasVariety, Kikai language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kikai language Context triple: [Northern Ryukyuan language, hasVariety, Kikai language]
-
A.
Kiga language
The Kiga language is a Bantu language spoken primarily by the Bakiga people of southwestern Uganda.
-
B.
Keiga language
The Keiga language is a Kadu (Kadugli) language spoken by the Keiga people in the Nuba Mountains region of Sudan.
-
C.
Kitanemuk language
The Kitanemuk language is an extinct Uto-Aztecan language once spoken by the Kitanemuk people of Southern California.
-
D.
Hiaki language
Hiaki language is an Uto-Aztecan language spoken primarily by the Yaqui (Hiaki) people of northern Mexico and the southwestern United States.
-
E.
Kioko language
The Kioko language is an Austronesian language of the Muna–Buton subgroup spoken by a small community in southeastern Sulawesi, Indonesia.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kikai language Triple: [Northern Ryukyuan language, hasVariety, Kikai language]
Generated description
The Kikai language is a Ryukyuan language spoken on Kikai Island in Japan’s Kagoshima Prefecture, known for its distinct dialectal variation and endangered status.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kikai language Target entity description: The Kikai language is a Ryukyuan language spoken on Kikai Island in Japan’s Kagoshima Prefecture, known for its distinct dialectal variation and endangered status.
-
A.
Kiga language
The Kiga language is a Bantu language spoken primarily by the Bakiga people of southwestern Uganda.
-
B.
Keiga language
The Keiga language is a Kadu (Kadugli) language spoken by the Keiga people in the Nuba Mountains region of Sudan.
-
C.
Kitanemuk language
The Kitanemuk language is an extinct Uto-Aztecan language once spoken by the Kitanemuk people of Southern California.
-
D.
Hiaki language
Hiaki language is an Uto-Aztecan language spoken primarily by the Yaqui (Hiaki) people of northern Mexico and the southwestern United States.
-
E.
Kioko language
The Kioko language is an Austronesian language of the Muna–Buton subgroup spoken by a small community in southeastern Sulawesi, Indonesia.
- F. None of above. chosen
Provenance (5 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_69e2458750b481908a8e4cf4609cc6cf |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17eb8b3588190b2bc8e7021f9ef10 |
completed | April 29, 2026, 3:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0ba7be4c7c81908ce5d01eb2926aea |
completed | May 18, 2026, 11:58 p.m. |
| NEDg | Description generation | batch_6a0ba8bb77bc81909c5422f9d73c1e70 |
completed | May 19, 2026, 12:03 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0ba94752c48190a8892cac5ef862b2 |
completed | May 19, 2026, 12:05 a.m. |
Created at: April 17, 2026, 3:36 p.m.