Triple
T7487151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dimasa Kingdom |
E176909
|
entity |
| Predicate | language |
P15
|
FINISHED |
| Object | Dimasa language |
E166026
|
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: Dimasa language | Statement: [Dimasa Kingdom, language, Dimasa language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dimasa language Context triple: [Dimasa Kingdom, language, Dimasa language]
-
A.
Dimasa language
chosen
Dimasa is a Tibeto-Burman language spoken primarily by the Dimasa people in the Indian states of Assam and Nagaland.
-
B.
Damana language
The Damana language is an indigenous Chibchan tongue spoken by the Wiwa people of the Sierra Nevada de Santa Marta region in northern Colombia.
-
C.
Madura language
The Madura language is an Austronesian language spoken primarily on Madura Island and in parts of East Java, Indonesia, by the Madurese people.
-
D.
Bima language
Bima language is an Austronesian language spoken primarily on Sumbawa Island in Indonesia, known for its distinct grammar and vocabulary within the region.
-
E.
Betawi language
Betawi language is an Austronesian language variety spoken primarily in Jakarta, Indonesia, known for blending Malay with influences from Javanese, Sundanese, Chinese, Arabic, and Dutch.
- 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_69c69f24ac508190bb98fe927c0bd065 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f5582adc81908b68439762965d88 |
completed | March 27, 2026, 9:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c845fd62dc8190a64f5464a204c0d2 |
completed | March 28, 2026, 9:19 p.m. |
Created at: March 27, 2026, 3:43 p.m.