Triple
T7124535
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dimasa language |
E166026
|
entity |
| Predicate | closelyRelatedTo |
P37
|
FINISHED |
| Object |
Garo language
The Garo language is a Tibeto-Burman language spoken primarily by the Garo people of northeastern India and neighboring Bangladesh.
|
E644025
|
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: Garo language | Statement: [Dimasa language, closelyRelatedTo, Garo language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Garo language Context triple: [Dimasa language, closelyRelatedTo, Garo language]
-
A.
Gurma language
Gurma language is a Gur language spoken primarily in parts of Burkina Faso, Togo, Benin, and neighboring West African countries.
-
B.
Sanglechi language
The Sanglechi language is an Eastern Iranian language spoken by a small community in the Sanglech Valley region of Afghanistan and Tajikistan.
-
C.
Murle language
The Murle language is an Eastern Sudanic language spoken primarily by the Murle people of South Sudan.
-
D.
Saho language
The Saho language is an Afroasiatic Cushitic language spoken primarily by the Saho people in Eritrea and northern Ethiopia.
-
E.
Agutaynen language
Agutaynen is an Austronesian language spoken by the Agutaynen people of Palawan in the Philippines.
- 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: Garo language Triple: [Dimasa language, closelyRelatedTo, Garo language]
Generated description
The Garo language is a Tibeto-Burman language spoken primarily by the Garo people of northeastern India and neighboring Bangladesh.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Garo language Target entity description: The Garo language is a Tibeto-Burman language spoken primarily by the Garo people of northeastern India and neighboring Bangladesh.
-
A.
Gurma language
Gurma language is a Gur language spoken primarily in parts of Burkina Faso, Togo, Benin, and neighboring West African countries.
-
B.
Sanglechi language
The Sanglechi language is an Eastern Iranian language spoken by a small community in the Sanglech Valley region of Afghanistan and Tajikistan.
-
C.
Murle language
The Murle language is an Eastern Sudanic language spoken primarily by the Murle people of South Sudan.
-
D.
Saho language
The Saho language is an Afroasiatic Cushitic language spoken primarily by the Saho people in Eritrea and northern Ethiopia.
-
E.
Agutaynen language
Agutaynen is an Austronesian language spoken by the Agutaynen people of Palawan in the Philippines.
- 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_69c6888350588190870cd552b427a1cd |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e64c0f688190a9b7482d86c2f033 |
completed | March 27, 2026, 8:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7a331ff988190886bde89035623c0 |
completed | March 28, 2026, 9:45 a.m. |
| NEDg | Description generation | batch_69c7a46d95b88190bbadf3e8d1788489 |
completed | March 28, 2026, 9:50 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7a52e6a1c8190bf45e0aa7a920baf |
completed | March 28, 2026, 9:53 a.m. |
Created at: March 27, 2026, 2:44 p.m.