Analog backscatter communication facilitates ultra- low-power wireless sensing by communicating using reflected radio frequency (RF) signals rather than generating their own at vastly reduced power consumption in the microwatt range. The reduced power consumption makes analog backscatter tags suitable for battery-free applications in the Internet-of-Things (IoT), with the caveat of limited querying and management capabilities when multiple tags are present in the same envi- ronment. These limitations stem from the inherent constraints of analog designs, which lack sophisticated addressing and multiple access techniques commonly found in digital systems that require power-hungry digital circuitry. In this paper, we present Chord, a novel querying mechanism that scales effectively with the number of analog backscatter tags. Our approach leverages frequency selective querying using multi-carrier excitation signals combined with combinatorial filtering at the tags to enable precise targeting of individual devices. This mechanism allows the reader to query specific tags by transmitting signals at their designated frequency sets, significantly reducing interference and collisions. Compared to O(N) querying complexity in traditional methods that require N separate querying frequencies, our approach achieves O(logN) complexity, significantly enhancing scalability for large deployments of distributed analog backscatter systems.