Triple
T9319086
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palaungic languages |
E224199
|
entity |
| Predicate | hasLanguage |
P15
|
FINISHED |
| Object | Danau language |
E775502
|
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: Danau language | Statement: [Palaungic languages, hasLanguage, Danau language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Danau language Context triple: [Palaungic languages, hasLanguage, Danau language]
-
A.
Danau language
chosen
The Danau language is a lesser-known Austroasiatic language spoken by the Danau people in parts of Myanmar.
-
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.
Dimasa language
Dimasa is a Tibeto-Burman language spoken primarily by the Dimasa people in the Indian states of Assam and Nagaland.
-
D.
Uduk language
The Uduk language is a Nilo-Saharan language spoken primarily by the Uduk people of eastern Sudan and western Ethiopia.
-
E.
Daakaka language
The Daakaka language is an Oceanic language spoken by communities on Ambrym Island in Vanuatu.
- 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_69ca8426d48481909596360f7791c7dd |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd358c7d348190a10fd8670d7756f5 |
completed | April 1, 2026, 3:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0c7c1fc848190bbb3ef6a1ed7a7d2 |
completed | April 4, 2026, 8:11 a.m. |
Created at: March 30, 2026, 7:38 p.m.