Triple
T9770837
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dimasa |
E237118
|
entity |
| Predicate | closelyRelatedTo |
P37
|
FINISHED |
| Object | Garo language |
E644025
|
NE FINISHED |
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: Garo language | Statement: [Dimasa, closelyRelatedTo, Garo language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Garo language Context triple: [Dimasa, closelyRelatedTo, Garo language]
-
A.
Garo language
chosen
The Garo language is a Tibeto-Burman language spoken primarily by the Garo people of northeastern India and neighboring Bangladesh.
-
B.
Gurma language
Gurma language is a Gur language spoken primarily in parts of Burkina Faso, Togo, Benin, and neighboring West African countries.
-
C.
Sanglechi language
The Sanglechi language is an Eastern Iranian language spoken by a small community in the Sanglech Valley region of Afghanistan and Tajikistan.
-
D.
Murle language
The Murle language is an Eastern Sudanic language spoken primarily by the Murle people of South Sudan.
-
E.
Saho language
The Saho language is an Afroasiatic Cushitic language spoken primarily by the Saho people in Eritrea and northern Ethiopia.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca84d831b8819090322686b47887ce |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda0f329148190a5e531478bc18073 |
completed | April 1, 2026, 10:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1bd0cae548190a2d9b42ea4ecc372 |
completed | April 5, 2026, 1:38 a.m. |
Created at: March 30, 2026, 8:26 p.m.