Triple
T2873279
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shan |
E56815
|
entity |
| Predicate | language |
P15
|
FINISHED |
| Object |
Shan language
Shan language is a Tai-Kadai language spoken primarily by the Shan people in Myanmar, with communities also in neighboring Thailand and China.
|
E304687
|
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: Shan language | Statement: [Shan, language, Shan language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shan language Context triple: [Shan, language, Shan language]
-
A.
Kangjia language
The Kangjia language is a lesser-known Mongolic language spoken by the Kangjia people in parts of northwestern China.
-
B.
Kavalan language
The Kavalan language is an endangered Austronesian language of the indigenous Kavalan people of northeastern Taiwan.
-
C.
Hezhen language
The Hezhen language is a critically endangered Tungusic language spoken by the Hezhen (Nanai) people of northeastern China along the Amur and Ussuri rivers.
-
D.
Siwu language
The Siwu language is a Niger-Congo language spoken primarily in the Volta Region of Ghana by the Mawu people.
-
E.
Lipan language
The Lipan language is an extinct Southern Athabaskan language once spoken by the Lipan Apache people of the southern Great Plains and northern Mexico.
- 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: Shan language Triple: [Shan, language, Shan language]
Generated description
Shan language is a Tai-Kadai language spoken primarily by the Shan people in Myanmar, with communities also in neighboring Thailand and China.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Shan language Target entity description: Shan language is a Tai-Kadai language spoken primarily by the Shan people in Myanmar, with communities also in neighboring Thailand and China.
-
A.
Kangjia language
The Kangjia language is a lesser-known Mongolic language spoken by the Kangjia people in parts of northwestern China.
-
B.
Kavalan language
The Kavalan language is an endangered Austronesian language of the indigenous Kavalan people of northeastern Taiwan.
-
C.
Hezhen language
The Hezhen language is a critically endangered Tungusic language spoken by the Hezhen (Nanai) people of northeastern China along the Amur and Ussuri rivers.
-
D.
Siwu language
The Siwu language is a Niger-Congo language spoken primarily in the Volta Region of Ghana by the Mawu people.
-
E.
Lipan language
The Lipan language is an extinct Southern Athabaskan language once spoken by the Lipan Apache people of the southern Great Plains and northern Mexico.
- 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_69ab4a4ced288190ab6d3e062d10f7f6 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abdfe59ef88190b8bdfdd03e8965f3 |
completed | March 7, 2026, 8:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b01db40e388190a208fe58e2ed6029 |
completed | March 10, 2026, 1:33 p.m. |
| NEDg | Description generation | batch_69b01f8745948190b4821aac1941276c |
completed | March 10, 2026, 1:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b020482e548190ab837025540673f7 |
completed | March 10, 2026, 1:44 p.m. |
Created at: March 6, 2026, 10:03 p.m.