Triple
T3159399
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iranian plateau |
E66067
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Dasht-e Kavir |
E309821
|
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: Dasht-e Kavir | Statement: [Iranian plateau, contains, Dasht-e Kavir]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dasht-e Kavir Context triple: [Iranian plateau, contains, Dasht-e Kavir]
-
A.
Dasht-e Kavir
chosen
Dasht-e Kavir is Iran’s vast central salt desert, characterized by arid plains, salt flats, and extreme climatic conditions.
-
B.
Karakum Desert
The Karakum Desert is a vast arid region covering much of Turkmenistan, known for its extreme climate, sparse population, and significant oil and natural gas reserves.
-
C.
Dasht-e Lut
Dasht-e Lut is a vast desert in southeastern Iran known as one of the hottest and driest places on Earth.
-
D.
Taklamakan Desert
The Taklamakan Desert is a vast, arid sand desert in China’s Xinjiang region, known for its extreme dryness, shifting dunes, and historical role along the Silk Road.
-
E.
Kyzylkum Desert
The Kyzylkum Desert is a vast arid region of sandy plains and dunes located between the Amu Darya and Syr Darya rivers in Central Asia, primarily within Uzbekistan, Kazakhstan, and Turkmenistan.
- 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_69ad85850c1481908a9e9c6242238de2 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada5ed82a08190a1bdcf18ee593c79 |
completed | March 8, 2026, 4:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b28e24fef881908b9b9d9a67c42c0e |
completed | March 12, 2026, 9:57 a.m. |
Created at: March 8, 2026, 3:05 p.m.