Triple
T2101570
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Turkic languages |
E37102
|
entity |
| Predicate | hasMajorLanguage |
P207
|
FINISHED |
| Object | Salar |
E103032
|
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: Salar | Statement: [Turkic languages, hasMajorLanguage, Salar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Salar Context triple: [Turkic languages, hasMajorLanguage, Salar]
-
A.
Salar
chosen
Salar is a Turkic ethnic group primarily residing in northwestern China, known for speaking the Salar language and practicing Islam.
-
B.
Khora
Khora is one of the now nearly extinct indigenous languages once spoken by the Great Andamanese people of the Andaman Islands in India.
-
C.
Taba
Taba is a small Egyptian resort town on the Red Sea near the border with Israel, known for its beaches, coral reefs, and role as a popular gateway between the two countries.
-
D.
Salar de Arizaro
Salar de Arizaro is one of the largest high-altitude salt flats in Argentina, known for its vast barren landscape and striking geological formations such as the Cono de Arita.
-
E.
Lota
Lota is a coastal city in southern Chile known historically for its coal mining industry and maritime heritage.
- 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_69a8861828948190924aa30c08806b3a |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abbabc83a8819091f786f21d33b5a6 |
completed | March 7, 2026, 5:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae3065f3588190bc483e07dda8cf71 |
completed | March 9, 2026, 2:28 a.m. |
Created at: March 4, 2026, 7:43 p.m.