Triple
T11182140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blackfoot language |
E264566
|
entity |
| Predicate | hasDialect |
P4251
|
FINISHED |
| Object |
Siksiká dialect
The Siksiká dialect is a variety of the Blackfoot language traditionally spoken by the Siksiká (Blackfoot) people of the northern Great Plains in Canada.
|
E910115
|
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: Siksiká dialect | Statement: [Blackfoot language, hasDialect, Siksiká dialect]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Siksiká dialect Context triple: [Blackfoot language, hasDialect, Siksiká dialect]
-
A.
Mriak-Mriku dialect
The Mriak-Mriku dialect is a regional variety of the Sasak language spoken by communities on the island of Lombok in Indonesia.
-
B.
Hunza dialect
The Hunza dialect is a regional variety of the Burushaski language spoken primarily in the Hunza Valley of northern Pakistan.
-
C.
Malgavet dialect
The Malgavet dialect is a regional variety of the Lihir language spoken on the Lihir Islands of Papua New Guinea.
-
D.
Aknogai dialect
The Aknogai dialect is a regional variety of the Nogai language spoken by Nogai communities in the North Caucasus.
-
E.
Akusha dialect
The Akusha dialect is a principal standardized variety of the Dargin language spoken in Dagestan, Russia.
- 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: Siksiká dialect Triple: [Blackfoot language, hasDialect, Siksiká dialect]
Generated description
The Siksiká dialect is a variety of the Blackfoot language traditionally spoken by the Siksiká (Blackfoot) people of the northern Great Plains in Canada.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Siksiká dialect Target entity description: The Siksiká dialect is a variety of the Blackfoot language traditionally spoken by the Siksiká (Blackfoot) people of the northern Great Plains in Canada.
-
A.
Mriak-Mriku dialect
The Mriak-Mriku dialect is a regional variety of the Sasak language spoken by communities on the island of Lombok in Indonesia.
-
B.
Hunza dialect
The Hunza dialect is a regional variety of the Burushaski language spoken primarily in the Hunza Valley of northern Pakistan.
-
C.
Malgavet dialect
The Malgavet dialect is a regional variety of the Lihir language spoken on the Lihir Islands of Papua New Guinea.
-
D.
Aknogai dialect
The Aknogai dialect is a regional variety of the Nogai language spoken by Nogai communities in the North Caucasus.
-
E.
Akusha dialect
The Akusha dialect is a principal standardized variety of the Dargin language spoken in Dagestan, Russia.
- 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_69d6aa9dafac8190bd90d2c74f661aa7 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8a7f35481909f35feb94ef10e80 |
completed | April 9, 2026, 5:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e483affa988190bb7dc4f74d8e878c |
completed | April 19, 2026, 7:26 a.m. |
| NEDg | Description generation | batch_69e48717c35481908fb05597084167e7 |
completed | April 19, 2026, 7:41 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e48875faa88190af33654e6d9a708b |
completed | April 19, 2026, 7:47 a.m. |
Created at: April 8, 2026, 9:29 p.m.